JP2022538125A - Filters for removal of multiple sclerosis-associated T cells - Google Patents

Abstract

Biological filters are described for removing target components from biological fluids, such as removal of pathogenic cells from whole blood. A filter includes a medium comprising an inert surface, and the entrapped material can be placed on the inert surface. Filters can be configured to selectively recognize, trap, and remove target cells, such as pathogenic cells associated with diseases such as autoimmune diseases or cancer. Also provided herein are devices, systems, apparatus, computer readable media, and offerings related to biological filtration.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application supersedes U.S. Provisional Patent Application No. 62/867,594 (filed June 27, 2019) and U.S. Provisional Patent Application No. 62/875,193 (filed July 17, 2019) , the entire contents of each of which are hereby incorporated by reference into this application.
Technical field

The present disclosure relates generally to devices, systems and methods for removing components of biological fluids. In some applications, the devices, systems and methods are used for diseases such as, but not limited to, autoimmune diseases, cancer, other immune system-related disorders or diseases, and complications associated with transplantation. obtain. More particularly, the present disclosure relates to devices, systems and methods for treating disease by altering the cellular composition of a patient's blood.

Background Autoimmune diseases are diseases in which the immune system recognizes self-antigens as foreign and attacks the body. This can occur in a wide range of diseases, from organ-specific diseases (eg thyroid and pancreatic diseases) to systemic diseases (eg systemic lupus erythematosus). Current treatments for autoimmune diseases focus on systemic immunosuppression, which can have significant side effects and can make patients more susceptible to infections.

Multiple sclerosis (MS) is an example of a chronic progressive autoimmune disease that attacks to varying degrees the myelinated axons of the central nervous system (CNS), causing slow progression and significant disability. is. Multiple sclerosis impairs patient quality of life. In fact, about 30% of people with multiple sclerosis will be wheelchair bound or have other severe disabilities. There are approximately 3 million people worldwide with multiple sclerosis. In the United States alone, nearly 10,000 new cases of multiple sclerosis are diagnosed each year, increasing the economic and social burden. In most patients, the disease begins as a paroxysmal disorder that progresses over time to a progressive disorder. There are four patterns of multiple sclerosis. Clinically Isolated Syndrome (CIS) is the first seizure with neurologic symptoms lasting longer than 24 hours. In some cases, there may be no further neurological symptoms, but in other cases it is later found that CIS was the first sign of multiple sclerosis. Another multiple sclerosis pattern is relapsing-remitting multiple sclerosis (RRMS), which is characterized by remission followed by acute attacks but no disease progression. When this form becomes progressive, it is called secondary progressive multiple sclerosis (SPMS). Primary Progressive Multiple Sclerosis (PPMS) is progressive from the beginning.

Current treatments for multiple sclerosis are primarily pharmacological. These treatments are associated with toxic effects, systemic immunosuppression, and rash, fever, chills, cough, chest pain, abdominal pain, diarrhea, flushing, nausea, pneumonia, progressive multifocal leukoencephalopathy (PML 1:1000), headache, Depression, bradycardia, lymphopenia, bronchitis, diarrhea, back pain, severe headache, hypertension, transient bradycardia, immunosuppression, pruritus, renal dysfunction, increased liver enzymes, acute coronary syndrome ( ACS), sarcoma (in animal models), and death. Pharmacological treatment only slightly reduces the frequency of attacks and generally does not permanently stop disease progression.

In the United States, a new patient is diagnosed with blood or bone marrow cancer about every three minutes. Examples of blood and bone marrow cancers are leukemia, lymphoma, myeloma, myelodysplastic syndrome (MDS), and myeloproliferative neoplasm (MPN). New cases of leukemia, lymphoma and myeloma are estimated to account for 10% of newly diagnosed cancer cases in the United States. Many types of lymphomas and leukemias, including highly aggressive forms such as adult T-cell leukemia/lymphoma, are associated with neoplasms of leukocytes such as natural killer (NK) cells, T cells and B lymphocytes. In recent years, cancer immunology, the artificial stimulation of the immune system to fight cancer, has been presented as an attractive and innovative alternative to conventional therapies such as surgery, radiotherapy and chemotherapy. However, this approach may not reach its full potential in treating tumors in which the patient's immune cells themselves are cancerous.

In view of the foregoing, it is clear that there remains a need for alternative therapies for debilitating diseases such as autoimmune diseases and cancer.

SUMMARY OF ASPECTS OF THE DISCLOSURE Some aspects of the present disclosure relate to biological filters. Consistent with disclosed embodiments, the biological filter comprises an inert surface medium, a human leukocyte antigen (HLA) protein disposed on the inert surface medium, an antigen bound to the HLA protein on the inert surface medium. It may contain peptides. Here, the antigenic peptide and HLA protein are selected to allow antigen-specific T cell receptors to bind to the antigenic peptide and HLA protein complex, thereby allowing T cells to , antigen-specific T cells can be immobilized to an inert surface medium via complexes.

In another aspect, the present disclosure relates to a biological filter that can be configured for cytoreduction of multiple sclerosis-associated T cells. The filter may comprise a filter medium for hosting substances that selectively bind to antigen-specific T-cell receptors, wherein the host material has been selected to bind to myelin-specific T-cell receptors. It contains a human leukocyte antigen (HLA)-myelin-peptide complex, thereby allowing specific binding of T-cell populations that recognize the HLA-myelin-peptide complex.

In another aspect, the present disclosure relates to a device that can be configured to remove pathogenic T cells from a patient's blood. The device is a first stage area configured to hold a blood separation device for separating leukocytes from other fractions of whole blood, the blood separation device having an inlet, a leukocyte outlet, and other fractions. a first stage area having a blood fraction outlet configured to allow blood to be returned to the patient; and a first pump for conveying blood from the patient through the first stage area. Also comprising a second stage region configured to hold a biological filter comprising a human leukocyte antigen (HLA)-peptide complex and having one or more inlets and one outlet, wherein the first stage The region and second stage region are oriented to allow flow from the leukocyte outlet of the blood separation device to one or more inlets of the biological filter. The device includes a second pump for recirculating the leukocytes from one or more outlets of the biological filter to one or more inlets of the biological filter, and blood to the first stage region and the second stage region. A plurality of electrically controllable valves may be provided for directing. The processor of the device controls the first pump to cause blood to flow through the first stage area until a certain amount of white blood cells are separated and transported to the second stage area, where a certain amount of white blood cells are separated. can be configured to stop the first pump when it is transported to the second stage area. Alternatively, a second pump may be activated, controlling multiple valves to recirculate the amount of leukocytes through a biological filter for a time sufficient to separate pathogenic T cells from non-pathogenic leukocytes, resulting in non-pathogenic leukocytes. It can be configured to return pathogenic white blood cells to the patient.

In another aspect, the present disclosure relates to a tubing set that can be configured for use in removing pathogenic T cells from a patient's blood. The tubing set may include a blood separation device for use in separating leukocytes from other fractions of whole blood, the first stage region having an inlet, a leukocyte outlet, and a blood fraction outlet, human leukocytes. A biological filter comprising an antigen (HLA)-peptide complex can be included and has one or more primary inlets, one or more primary outlets, one or more recirculation inlets, and one or more recirculation outlets. a second stage region having a recirculation loop interconnecting one or more recirculation outlets with a recirculation inlet; one or more blood for conveying blood from the patient to one or more inlets of the first stage region; An extraction tube and one or more intermediate tubes for conveying blood from the leukocyte outlet of the first stage area to the primary inlet of the second stage area and the blood fraction from the blood fraction outlet of the first stage area for return to the patient. and one or more leukocyte return tubes for carrying leukocytes from the primary outlet of the second stage area for return to the patient.

In a further aspect, the present disclosure provides systems for predictively adjusting therapeutic regimens for patients with T cell-associated immune disorders. The system can include one or more processors to receive first data related to treatment of a plurality of patients sharing common HLA and common peptides that induce activation of disease-associated T cells. is set. Here, the first data involve the progression of common peptides that activate T cells over time, and during further progression of the disease, more different peptides activate disease-associated T cells than during the early stages. It is characterized by Also associated with a particular patient with common HLA and common peptides, and a first peptide set activates a first subpopulation of disease-associated T cells and a second peptide set of disease-associated T cells. A second data is received at a stage of the disease that does not activate the second subpopulation. Using the first data, determine that the second set of peptides in a particular patient corresponds to late disease progression. Remedial action is then taken to eliminate the second subpopulation of disease-associated T cells from the particular patient before the second set of peptides activates the second subpopulation of disease-associated T cells.

In another aspect, the disclosure relates to a method of removing specific T cells, pathogenic cells, or non-pathogenic cells from a patient. The method involves removing a biological fluid from a patient, which biological fluid may contain specific cells. Alternatively, the biological fluid may be extracorporeally flowed through a media host material that selectively binds only to specific cells, thereby capturing the specific cells with the media, and the biological fluid free of the captured specific cells may be transferred to the patient's body. can include returning to

In yet another aspect, the present disclosure relates to a method of generating a personalized biological filter for selectively removing pathogenic cells from a patient. The method comprises the steps of identifying a patient's human leukocyte antigen (HLA) type, identifying one or more immunogenic peptides associated with the patient's disease, identifying the patient's identified HLA type and one or more immune Recombinantly, synthetically or endogenously producing/making an HLA-peptide complex corresponding to the progenitor peptide and binding the HLA-peptide complex to the inert surface medium of the biological filter. can include steps. In another embodiment, a method of manufacturing a personalized biological filter for selectively removing pathogenic cells from a patient is contemplated, which method identifies the patient's human leukocyte antigen (HLA) type. identifying one or more immunogenic peptides associated with the patient's disease; recombinantly or endogenously producing HLA proteins corresponding to the identified HLA types of the patient; binding to an active surface medium, synthesizing one or more identified peptides associated with a patient's disease, and loading the identified peptides onto HLA proteins bound to an inert surface medium.

In a further aspect, the disclosure relates to a method of treating a patient. The method comprises the steps of determining a patient's human leukocyte antigen (HLA) type, identifying specific disease-associated peptides that cause T-cell receptor activation in the patient with the determined HLA, extracorporeally exposing the patient's blood to a filter treated with a complex composed of a disease-associated peptide loaded thereon, thereby causing the binding of T cells to the filter, and removing the bound T cells. returning to the patient's blood under condition. In some embodiments, the method may be directed to treating autoimmune disease in a patient. For example, the method may be directed to treating a patient with a T cell-associated autoimmune disease, for a particular patient with an autoimmune disease caused by a first T cell and not a second T cell. Obtaining human leukocyte antigen (HLA)-peptide complex data and comparing the HLA-peptide complex data for a particular patient with HLA-peptide complex data associated with a patient population having a T-cell associated pathology. , removing the second T cells from the particular patient before the autoimmune disease in the particular patient is induced by the second T cells. Here, the population data contain epitope spreading information suggesting that individuals with autoimmune diseases induced by a first T cell become induced by a second T cell over time.

In yet a further aspect, the disclosure relates to a method of estimating the amount of disease-specific pathogenic T cells in a patient. The method includes the steps of obtaining a first biological fluid sample from a patient, stripping native peptides from a first group of human leukocyte antigens (HLA) in the first biological fluid sample; comparing the one or more sequences with known information to identify one or more disease-specific peptide sequences among the natural peptides; incorporating on the peptide sequence and contacting the plurality of HLA-peptide complexes with a second biological fluid sample; Determining the amount of T cells that bind to the complex and, based on the measured amount of T cells that bind to multiple HLA-peptide complexes, the number of disease-specific pathogenic T cells in a biological fluid within the patient. A step of making a quantity estimate may be included.

Additional features and advantages of the disclosed embodiments will be set forth in part in the description that follows, and in part will be apparent from the description, or may be learned by practice of the disclosed embodiments. The features and advantages of the disclosed embodiments will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosed embodiments, which are set forth in the claims.

The accompanying drawings form part of the specification. The drawings illustrate several embodiments of the present disclosure and, together with the description, serve to explain the principles of the disclosed embodiments as recited in the appended claims.

FIG. 1 shows an exemplary biological filter assembly consistent with embodiments of the present disclosure.

FIG. 2A shows a sheet of inert surface media consistent with embodiments of the present disclosure.

FIG. 2B shows fibers of inert surface media consistent with embodiments of the present disclosure.

FIG. 2C shows a bead of inert surface media consistent with embodiments of the present disclosure.

FIG. 2D shows a sponge-like structure of inert surface media consistent with embodiments of the present disclosure.

FIG. 3 shows an exemplary layered arrangement of a multilayer filter consistent with embodiments of the present disclosure.

FIG. 4 is a schematic representation of an inert surface medium with HLA proteins bound thereto, consistent with embodiments of the present disclosure.

FIG. 5 is a schematic representation of HLA proteins attached via a maleimide linker to an inert surface medium consistent with embodiments of the present disclosure.

FIG. 6 is a schematic representation of the molecular pathogenesis of multiple sclerosis.

FIG. 7A shows a PDMS medium consistent with embodiments of the present disclosure.

FIG. 7B shows polycarbonate media consistent with embodiments of the present disclosure.

FIG. 7C shows an Ultem medium, consistent with embodiments of the present disclosure.

FIG. 7D shows a Tritane media consistent with embodiments of the present disclosure.

FIG. 8 shows a schematic diagram of an exemplary biological filter for cytoreduction of multiple sclerosis-associated T cells consistent with embodiments of the present disclosure.

FIG. 9 shows a schematic representation of myelin protein antigens bound to HLA I and HLA II, respectively, consistent with embodiments of the present disclosure.

FIG. 10 shows a schematic diagram of an exemplary two-step apparatus for removing pathogenic T cells from a patient's blood consistent with embodiments of the present disclosure.

FIG. 11A shows a schematic diagram of an exemplary apheresis blood separation device consistent with embodiments of the present disclosure.

FIG. 11B shows an exemplary centrifugal blood separation device consistent with embodiments of the present disclosure.

FIG. 11C shows an exemplary filtered blood separation device consistent with embodiments of the present disclosure.

FIG. 12A shows a schematic diagram of an exemplary two-stage tubing set for removing pathogenic T cells from a patient's blood consistent with embodiments of the present disclosure.

FIG. 12B shows a schematic diagram of an exemplary second stage region of a two stage tubeset consistent with embodiments of the present disclosure.

FIG. 12C shows a schematic diagram of an exemplary second stage region of a two stage tubeset consistent with embodiments of the present disclosure.

FIG. 12D shows a schematic diagram of an exemplary second stage region of a two stage tubeset consistent with embodiments of the present disclosure.

FIG. 13 is a schematic diagram of a system that may be used to implement methods consistent with some embodiments of the present disclosure.

FIG. 14 is a block diagram of an exemplary preprocessing method consistent with this disclosure.

FIG. 15 shows an exemplary method for removing specific cells from a biological fluid consistent with embodiments of the present disclosure.

FIG. 16 shows a schematic representation of a specific cell-trapping media host material consistent with embodiments of the present disclosure.

FIG. 17A shows a schematic representation of a medium hosting HLA-peptide complexes consistent with embodiments of the present disclosure.

FIG. 17B shows a schematic representation of a vehicle-hosted antibody consistent with embodiments of the present disclosure.

FIG. 18 illustrates in block form various steps of an exemplary method of manufacturing a personalized biological filter for selective removal of pathogenic cells consistent with embodiments of the present disclosure.

FIG. 19 illustrates, in block form, an exemplary method for using HLA-peptide complexes to extracorporeally remove T cells from a patient's blood consistent with embodiments of the present disclosure.

FIG. 20A shows a schematic representation of an HLA pentamer consistent with embodiments of the present disclosure.

FIG. 20B shows a schematic representation of HLA tetramers consistent with embodiments of the present disclosure.

FIG. 21A shows a schematic representation of HLA I linked to a fluorophore consistent with embodiments of the present disclosure.

FIG. 21B shows a schematic diagram of HLA II linked to an enzyme consistent with embodiments of the present disclosure.

FIG. 22A shows a schematic diagram of removing bound T cells from a filter consistent with embodiments of the present disclosure.

FIG. 22B shows a schematic of the process of fluorescence-activated cell sorting consistent with embodiments of the present disclosure.

FIG. 23 shows, in block form, various steps of an exemplary method of treating a patient with a T cell-related autoimmune disease consistent with embodiments of the present disclosure.

FIG. 24 shows a flowchart of a process for depleting T cells consistent with embodiments of the present disclosure.

FIG. 25 shows in block diagram form a method for estimating pathogenic T cells in a patient consistent with embodiments of the present disclosure.

FIG. 26 is a FACS histogram showing single staining of T cells in lymph nodes with Thy1.2 after in-vitro incubation, consistent with disclosed embodiments. Positive staining for Thy1.2 (LF4-H) is shown in the lower right quadrant (26.88%).

The figure shows double staining of MOG-activated T cells with a T lymphocyte marker (Thy1.2-APC) before isolation and already conjugated to PE (protein-PE), consistent with disclosed embodiments. FACS histogram showing staining for protein (protein-PE).

Figures 28A and 28B are FACS histograms showing the number of MOG-activated T cells that did not adhere to the column after separation from protein complexes consistent with disclosed embodiments.

Figures 29A and 29B are FACS histograms showing the number of MOG-activated T cell binding within columns after separation with protein complexes consistent with disclosed embodiments.

Figure 30A is a representative SDS-PAGE of BIX.XX-GGC protein after purification under reducing (-DTT) and non-reducing (+DTT) conditions consistent with disclosed embodiments.

FIG. 30B is a representative CD spectrum of BIX.XX-GGC protein consistent with disclosed embodiments.

FIG. 31 shows a schematic of a silicon wafer coating procedure consistent with disclosed embodiments.

FIG. 32A schematically shows a silicon wafer coated with BIX.XX-GGC protein in a 1 μm×1 μm field consistent with the disclosed embodiment (AFM scan).

FIG. 32B schematically shows a silicon wafer coated with BIX.XX-GGC protein in a 10 μm×10 μm field consistent with the disclosed embodiment (AFM scan).

Figures 33A-33D are graphs showing post-filtration clinical scores in the rat EAE model (scored on a scale of 0-5), consistent with disclosed embodiments; Measurement scores on day (Figure 33B), day 5 (Figure 33C) and day 6 (Figure 33D) are shown.

FIGS. 34A-34D are graphs showing post-filtration day-adjusted clinical scores in a rat EAE model (scored on a scale of 0-5), consistent with disclosed embodiments; Figure 34A) shows the measured scores on day 4 (Figure 34B), day 5 (Figure 34C) and day 6 (Figure 34D) after treatment.

Figures 35A-35F are representative flow cytometric analyzes of human-derived PBMCs consistent with disclosed embodiments.

FIG. 36 is a table showing exemplary filtration to remove 42% of specific cells from PBMCs from multiple sclerosis patients consistent with disclosed embodiments.

Figures 37A and 37B show a filter surface with trapped cells consistent with the disclosed embodiments.

Figures 38A-38C are close-ups of filter surfaces after filtration of mouse cells consistent with the disclosed embodiments. Ditto.

FIG. 39 is a schematic representation of protein binding to membrane compositions, consistent with disclosed embodiments.

Figures 40A-40C show scanning electron microscopy (SEM) results of polysulfone-polyacrylic acid (PAA) fibrils consistent with disclosed embodiments.

Figures 41A and 42B are atomic force microscopy (AFM) results consistent with the disclosed embodiment, showing the polysulfone-poly(2-aminoethyl)acrylamide membrane alone (Figure 41A) and coated with protein. (Fig. 41B).

Figures 42A and 42B show atomic force microscopy (AFM) results of protein-activated silicon sheets consistent with disclosed embodiments.

FIG. 43 is a graph showing X-ray photoelectron spectroscopy (XPS) results of protein-activated PSf sheets consistent with disclosed embodiments.

DETAILED DESCRIPTION Exemplary embodiments are described with reference to the accompanying drawings. For convenience, the same reference numbers will be used throughout the drawings to refer to the same or similar parts. As a note to the reader, this detailed description includes a series of topic headings, which are not limiting in any way. Rather, it is intended that any aspect of the disclosure presented under any heading can be practiced in conjunction with any other aspect presented under the same or different heading. While examples and features of the disclosed principles are described herein, modifications, adaptations, and other forms of implementation are possible without departing from the spirit and scope of the disclosed embodiments. Also, "including" and "having" and other similar forms are equivalent in meaning, implying that the item presented before any of these words is an exhaustive listing of that item. and is not intended to be limited to only the items listed. Also note that as used in this disclosure and the appended claims, the singular forms "a,""the," etc. include plural references unless the context clearly dictates otherwise. want to be Further, part of this disclosure describes methods and structures together in examples, but it should be understood that the methods are not limited by the structures and the structures are not limited by the methods. Rather, it is contemplated that the methods can be practiced with structures other than those provided in the examples, and the structures can be used in ways different from those described. Further, where methods are described herein, such methods may be implemented in hardware, e.g., via one or more processors, and any such methods include computer readable media. It should be understood that it may also be implemented in software via Accordingly, the method disclosure herein similarly includes one or more processors configured to perform each method, as well as instructions for causing the one or more processors to perform each method. It is intended to constitute a disclosure of computer-readable media.
Summary of Aspects of the Disclosure

Aspects of the present disclosure relate to devices, apparatus, computer readable media, systems and methods involving the removal of components of biological material. Embodiments disclosed herein can be used to treat autoimmune diseases, cancers (including solid tumors and blood or bone marrow cancers), and/or post-transplant complications such as graft-versus-host disease (GVHD). It can be used to treat diseases. Embodiments of the present disclosure utilize specific MHC or HLA molecules, load disease-specific peptides onto the HLA groove, and utilize disease-specific peptides based on T-cell receptor (TCR) recognition from any type of biological fluid. A biological filter that identifies, traps and removes pathogenic T cell clones can be included.

As used herein, "major histocompatibility complex" (MHC) is a group of genes encoding proteins found on the surface of cells that help the immune system, particularly T cells, to recognize foreign substances. MHC proteins are found in all higher vertebrates. In humans, this complex is also called the "human leukocyte antigen" (HLA) system. The terms MHC and HLA are used interchangeably throughout the disclosure. HLA proteins are typically found on the surface of human cells, involved in the regulation of an individual's immune system. For example, HLA proteins can function by recognizing foreign, non-self materials within an individual and initiating an immune response that neutralizes those materials. Foreign, non-self material can be incorporated into HLA complexes and presented to the individual's immune system in order to initiate or stimulate the individual's immune response. Each individual has a specific set, or type, of HLA proteins. In some embodiments, an individual's HLA type can be identified using standard laboratory techniques in an accredited clinical laboratory. For example, identifying an individual's HLA type can include analyzing a blood sample taken from the individual. Alternatively, an individual's HLA type may be identified by other suitable means.

As used herein, "pathogenic," when referring to cells, includes both pathogenic cells and cell fragments, as well as other particles whose removal may improve the patient's clinical condition. Non-limiting examples of pathogenic cells include T cells reactive to myelin basic protein (MBP) in patients with multiple sclerosis, T cells that stimulate immune responses to allogeneic or autologous transplantation, and disease-associated They are secreted particles or cells that are abundant in biological fluids. The term pathogenic cells also refers to abnormally high numbers of healthy cells.

In certain embodiments, biological filters consistent with the present disclosure convert HLA monomers or multimers (e.g., dimers, tetramers, pentamers, dextramers) into soluble forms (e.g., HLA I or HLA II), which may be in intact form (i.e., intact polypeptide) or truncated form (i.e., truncated polypeptide), and capture moieties of any kind (e.g., peptide or an epitope thereof). In another example, these molecules can be injected intravenously to recognize, capture and eliminate specific T cell clones. One to several hours after injection, the patient can be connected to any filter using a unique filter consistent with this disclosure. Filters may include special surfaces/molecules/reagents that react with small capture molecules bound to HLA monomers or multimers. This can result in capture of a significant amount (or substantially all) of HLA monomers or multimers from the blood by the filter. The remaining blood components can be returned to the patient intact.

The methods described herein identify, capture and capture specific T cell clones based on T cell receptor (TCR) recognition without immobilizing HLA-peptide complexes to any surface or media filter. can include removing. For example, HLA molecules may be provided in solution or other media other than a surface or physical filter media.

T cells and autoimmune diseases

The immune system is made up of several types of cells, including T cells. Certain T cells also mediate autoimmune diseases such as multiple sclerosis (MS) and insulin-dependent diabetes mellitus (IDDM). In both diseases, specific organs are damaged. In multiple sclerosis, an important component of the central nervous system (CNS) called myelin is targeted for damage, whereas in IDDM the insulin-producing pancreas is damaged until the body can no longer produce insulin. . These damages result from the immune system misrecognizing self proteins as pathogens (non-self).

Higher amounts of peripheral T cells can be observed in the peripheral blood of patients with autoimmune diseases, especially in multiple sclerosis patients compared to healthy individuals. Furthermore, T cells from patients with multiple sclerosis have a low activation threshold, high proliferation rates, and high survival rates.

Given these observations, some embodiments of the present disclosure seek to deplete disease-specific pathogenic T cells from patient blood. These specific T cells are the T cells that are directly involved in tissue damage and disease states. In the case of multiple sclerosis, this removal is performed to significantly slow disease progression and prevent neurological tissue damage in multiple sclerosis patients. The capture of these T cells by filters is based on the presence of special receptors expressed on T cells called T cell receptors (TCRs). Harmful T cells are characterized by T cell receptors that recognize components of myelin (ie, peptides). Recognition and binding of myelin peptides by the T-cell receptors of T-cells can be achieved by the binding of the peptides onto the HLA complex. Thus, a biological filter consistent with the disclosed embodiments can include a layer of HLA complex molecules with bound myelin peptides. Harmful T cells involved in disease progression bind to and are removed from the filter. This filtration technology offers a non-pharmacological solution for treating diseases like multiple sclerosis and is more commonly used to remove other components of biological material. good too.

For example, similar isolation-based therapies consistent with this disclosure may be used to treat other autoimmune diseases. Examples of such other autoimmune diseases that can be treated using the embodiments disclosed herein include achalasia, Addison's disease, adult Still's disease, agammaglobulinemia, alopecia areata, amyloidosis , ankylosing spondylitis, anti-GBM/anti-TBM nephritis, antiphospholipid syndrome, autoimmune angioedema, autoimmune autonomic imbalance, autoimmune encephalomyelitis, autoimmune hepatitis, inner ear autoimmune disease ( AIED), autoimmune myocarditis, autoimmune oophoritis, autoimmune orchitis, autoimmune pancreatitis, autoimmune retinopathy, autoimmune urticaria, axonal and neurogenic neuropathy (AMAN), Barrow's disease , Behcet's disease, benign mucous membrane pemphigoid, bullous pemphigoid, chronic inflammatory demyelinating polyneuropathy (CIDP), chronic relapsing polymyelitis (CRMO), Churg-Strauss syndrome (CSS) or favorable Acidophilic granulomatosis (EGPA), cicatricial pemphigoid, Cogan's syndrome, cold agglutinin disease, congenital heart block, coxsackie myocarditis, CREST syndrome, Crohn's disease, dermatitis herpetiformis, dermatomyositis, Devic's disease (neuromyelitis optica), discoid lupus, Dressler syndrome, endometriosis, eosinophilic esophagitis (EoE), eosinophilic fasciitis, erythema nodosum, mixed essential cryoglobulinemia, Evans syndrome, fibromyalgia, fibrous alveolitis, giant cell arteritis (temporal arteritis), giant cellitis, myocarditis, Goodpasture's syndrome, granulomatous polyangiitis, Graves' disease, Guillain-Barré syndrome, Hashimoto thyroiditis, hemolytic anemia, Henoch-Schoenlein purpura (HSP), herpes gestationis or pemphigoid gestationis (PG), hidradenitis suppurativa (HS) (acne), hypogammaglobulinemia, IgA nephropathy, IgG4-related sclerosing disease, immune thrombocytopenic purpura (ITP), inclusion body myositis (IBM), interstitial cystitis (IC), juvenile arthritis, juvenile diabetes or type 1 diabetes or insulin dependent diabetes mellitus (IDDM), juvenile myositis (JM), Kawasaki disease, Lambert-Eaton syndrome, leukocytoclastic vasculitis, lichen planus, lichen sclerosus, cellulitic conjunctivitis, linear IgA bullous disease (LAD) , lupus, chronic Lyme disease, Meniere's disease, microscopic polyangiitis (MPA), mixed connective tissue disease (MCTD), Mullen ulcer, acute pityriasis lichenoidosis (Mucha-Habermann disease), multifocal motor neuropathy (MMN) or MMNCB, multiple sclerosis, myasthenia gravis, myositis, narcolepsy, neonatal lupus, Neuromyelitis optica, neutropenia, ocular pemphigoid, optic neuritis, palindromic rheumatoid arthritis (PR), pediatric autoimmune neuropsychiatric disorders associated with streptococcal infection (PANDAS), neoplastic cerebellar degeneration (PCD) ), paroxysmal nocturnal hemoglobinuria (PNH), Parry-Romberg syndrome, pars planitis (uveitis peripheral), Parsonage-Turner syndrome, pemphigus, peripheral neuropathy, perivenous encephalomyelitis, pernicious anemia ( PA), POEMS syndrome, polyarteritis nodosa, polyglandular syndrome type I/II/III, polymyalgia rheumatoid arthritis, polymyositis, post-myocardial infarction syndrome, post-pericardiotomy syndrome, primary bile cirrhosis of the liver, primary sclerosing cholangitis, progesterone dermatitis, psoriasis, psoriatic arthritis, aplasia red cell (PRCA), pyoderma gangrenosum, Raynaud's phenomenon, reactive arthritis, reflex dystrophy, recurrent polychondritis , restless legs syndrome (RLS), retroperitoneal fibrosis, rheumatic fever, rheumatoid arthritis, sarcoidosis, Schmidt syndrome, scleritis, scleroderma, Sjögren's syndrome, autoimmune sperm/dysplasia/orchitis, Stiff-person syndrome (SPS), subacute bacterial endocarditis (SBE), Susac syndrome, sympathetic ophthalmia (SO), Takayasu arteritis, temporal arteritis/giant cell arteritis, thrombocytopenic purpura disease (TTP), Tolosa-Hunt syndrome (THS), transverse myelitis, ulcerative colitis (UC), undifferentiated connective tissue disease (UCTD), uveitis, vasculitis, vitiligo, Voigt-Koyanagi-Harada disease There is In one embodiment, the autoimmune disease is selected from multiple sclerosis, myasthenia gravis, type 1 diabetes, inflammatory bowel disease (eg, Crohn's disease, ulcerative colitis), and Lambert-Eaton syndrome.

Filtration-based treatment of biological fluids consistent with the present disclosure can also be applied to the treatment of various cancers, including solid tumors, among others, leukemia, lymphoma, myeloma, myelodysplastic syndrome, myeloproliferation. It can be applied to the treatment of blood cancers such as sexual neoplasms, polycythemia vera, or bone marrow cancers.

Some disclosed embodiments are useful for treating leukemia, acute leukemia (AL), other cancers, immune system related diseases and disorders, allergies, anaphylaxis, asthma, post-transplant rejection (including GVHD), post-transplant conditions, severe Myasthenia (MG), Lambert-Eaton syndrome, multiple sclerosis (MS), polycythemia vera (PCV), thrombocytosis, other myeloproliferative disorders, and pathological cell surface-expressing viral infections can be used in the treatment of
biological filter

Some aspects of the present disclosure relate to filters, including biological filters and methods of making biological filters. However, it should be noted that aspects of the disclosure in its broadest sense are not limited to biological filters. Rather, some aspects of the foregoing disclosure do not include filters, and other aspects of the disclosure can be applied to filters other than biological filters.

The term "biological filter" generally refers to any medium, regardless of form, that removes biological material from a biological fluid using biological mechanisms. By way of example, such filters may contain organic molecules such as proteins. Removal of biological material can occur via any biological or chemical process such as binding or reaction. One such mechanism may involve molecular binding. The filter may have any suitable form capable of removal function. For example, a filter may be configured to be in the form of or include one or more sheets of material to which biological fluid components bind, adhere, or otherwise react. or other structures that provide similar effects including, but not limited to, meshes, fibers, gels, beads, scaffolds, or any other material having a surface area configured for biological filtration. can be configured to Such filters can be configured to trap cells, proteins, nucleic acids, lipids, polysaccharides, or any other biological material. For example, filters may contain proteins or be immobilized with proteins that recognize and trap pathogenic or non-pathogenic cells, depending on the function the filter is designed to perform. In some embodiments, pathogenic cells may have the same role as non-pathogenic cells, except that they recognize and attack self-structures and substances. As an example, a filter may be designed to remove one or more of many pathogenic cells associated with many diseases. For example, filters may be designed to remove pathogenic lymphocytes.

By way of non-limiting example, FIG. 1 illustrates a biological filter that includes a housing 104, an inlet port 106 for directing the biological fluid inflow 108 into the housing 104, and an outlet port 110 for the biological fluid exiting the housing. 102 is shown, but not limited to this. Filtration media 114 may be contained within a housing, as described below. Although housing 104 is shown as cylindrical, the housing may be of any suitable shape and constructed of any suitable material.

Consistent with disclosed embodiments, the filter may include an inert surface medium. The term "inert" generally refers to a substance or material that does not alter, absorb, or react with non-specific particles, eg, non-defined cells or soluble particles. As used herein, the term "vehicle" can include any substance that can act as a base, support, or anchor for materials that selectively bind to cells. In other words, the medium "hosts" substances that selectively bind to cells. In some exemplary embodiments, the inert surface medium can include polysulfone. In other exemplary embodiments, the inert surface medium may comprise polysulfone derivatives, glass matrices, silicon matrices, polydimethylsiloxanes, polycarbonates, polyetherimides, tritans, or combinations of the above or others. In some embodiments, the inert surface medium may further comprise a polyelectrolyte alone or in combination with another material or other substance or material identified above. In other embodiments, the inert surface medium may comprise at least one of polyethylene glycol (PEG), PEG derivatives, polystyrene, avidin or streptavidin. Alternatively, the surface of the filter may be somewhat or highly absorbent, or reactive with non-specific particles.

FIGS. 2A-2D illustrate some non-limiting examples of inert surface media constructions that may be used to form a filter media, such as filter media 114 of FIG. FIG. 2A shows a sheet 202 of inert surface media. 2B shows fibers 204 of inert surface media. 2C shows a bead 206 of inert surface medium. FIG. 2D shows a sponge-like structure 208 of inert surface media. Other solid, semi-solid, or fluid materials can be used as inert surface media as long as they can serve as a base for the filtration media.

In certain embodiments, a filter can include multiple layers configured to allow fluid flow therebetween. Any layered structure may be used so long as the fluid can contact a sufficient portion of the filtration medium to achieve the intended filtration function. Thus, referring to FIGS. 2A-2D, for example, the layering of sheets 202, fibers 204, beads 206, or portions of sponge-like structure 208 with interstices configured to allow fluid flow therebetween. 1 is a non-limiting example of multiple layers formed. In the case of sponge-like structure 208, the portions on either side of the gap can be considered separate layers within the meaning of this disclosure.

Portions of adjacent layers may be in contact with each other or may be separated from each other by scaffolding, for example. FIG. 3 provides an example of spaced apart layers that allow fluid to flow between them, with the hatched area 302 representing the filtration media and the unhatched area 304 representing the fluid flow. represents the area that can be Region 304 may be a substantial void in the structure, or may include a porous or channel structure that allows fluid flow therein. As shown in FIG. 3, the layers of the multi-layer filter may be substantially flat, contoured, or arranged in a matrix of channelized rows and columns. Again, the particular structure is not necessarily critical in the broadest sense of this disclosure, so long as the structure is capable of enabling fluid to be filtered through contact with the filtration medium.

The housing or filtration media volume may be of any size, depending on the desired application specifications. In some embodiments, the housing or filtration media can be sized to allow one or more cycles of filtration and to allow batches of biological material to be circulated or recirculated through it.

In some embodiments, the housing and filter can be configured to allow flow of the biological fluid without damaging components of the biological fluid, such as cells. For example, the filter may be configured not to apply shear forces to the biological fluid flowing therethrough. In other embodiments, filters can be designed to adjust pressure regulation during fluid administration. In certain embodiments, the filter may be configured to prevent pressure build-up or pressure drop upon exposure to fluid. In some embodiments, the scaffolding of the filter can be sized to substantially prevent obstruction of flow. For example, the scaffold is sized to prevent fluid components such as blood clots, platelets, and protein aggregates from flowing or preferentially collecting in certain areas of the housing or filter. be able to.

In some embodiments, filtering may involve subjecting the biological sample to more than one filter. For example, two or more filters may be connected in series or in parallel with each other. In certain embodiments, each filter in a multi-filter system can be designed to capture a specific cell type, thus allowing capture of multiple cell types when subjecting a biological sample to the system. As an example, in a multifilter system having two filters, the first filter can be designed to capture CD8+ T cells and the second filter can be designed to capture CD4+ T cells. can be done. These are examples for illustrative purposes only, as filters can be designed to trap a host of biological components, depending on the intended design of the filter.

In some embodiments, filtration of biological material may be performed extracorporeally or outside the individual. As an example, filtration can be accomplished by withdrawing fluid from a vein of an individual, passing the fluid through a filter, and returning the fluid to either another vein or the same vein of the individual in a closed circuit. Alternatively, filtering can involve taking a sample from an individual, filtering the sample in a clinical laboratory, and returning the filtered sample to the individual. In another embodiment, the filter can be placed in a blood vessel within an individual's body. Such filters may be incorporated into vascular stents, with the stent serving as the host medium and the HLA-peptide complexes bound, for example, to the host medium. Such stent-based biological filters may be temporarily deployed via a balloon catheter or may be self-expanding, with the stent being removable after its filtering capacity is exhausted. . When deployed, the filter may be placed in proximity to, for example, a lymphatic organ or any other organ. In a further embodiment, an indwelling filter can be continuously attached to cells and replaced. For example, a port may be provided within the patient's vasculature and the removable filter may be accessible through the port. For example, the septum may have a replaceable biological filter component that traps pathogens that eventually allow the pathogens to be removed when the filter is replaced. In another example, a biological filter can be left in a patient's body and connected to the patient's vasculature in a manner similar to the proposed implantable artificial kidney. In some such embodiments, the filter may be left in place for an extended period of time with intermittent replacement of the filter. Alternatively, or additionally, biological filters may be modified within the body to minimize the need for more frequent replacement. Through injection of additional HLA-peptide conjugates, for example, fresh conjugates may bind to the already deposited filter media. In this way, additional filtering capacity can be achieved from already deployed filtering media. In yet another embodiment, a portable filter may be worn or carried by the patient, or with or without the use of an external pump, to allow extracorporeal blood flow through the filter. It can be placed adjacent to the patient's bed during sleep. Any of these embodiments can be used to achieve clinical results (e.g., clearance of pathogens to reduce disease symptoms) or to perform blood tests to measure specific pathogens or cellular levels. may be used for

Accordingly, the filter may include external elements. By way of example, the external element may be cylindrical, cylindrical, or shaped in any other suitable form so long as it can hold the filter media for its intended filtration purpose. The external element can be made of a biocompatible material such as polystyrene.

In some embodiments, a biological filter can include human leukocyte antigen (HLA) proteins disposed on an inert surface medium.

In some embodiments, HLA proteins are modified from endogenous HLA proteins. For example, HLA proteins may comprise at least one of monomers or multimers, and other modifications and additions, such as single amino acids, sequences of amino acids, HLA protein subunits, or multiple subunits. . In some embodiments, HLA proteins may be truncated or truncated from their full length. A truncated HLA protein can be further modified, for example, by adding one or more additional amino acid residues at either end of the truncated protein. As a non-limiting example, a truncated HLA protein can be altered by adding a cysteine as the C-terminal residue.

HLA proteins can be produced recombinantly. Alternatively or additionally, HLA proteins can be obtained endogenously from an individual, such as a patient. In certain embodiments, the recombinantly designed HLA proteins may comprise recombinant proteins similar to the patient's proteins. For example, HLA proteins can be HLA typed to match a patient. In some embodiments, the HLA protein can be HLA I or HLA II. In some embodiments, recombinantly designed HLA proteins may contain peptide binding grooves for binding to endogenous or synthetic peptides that may be subsequently presented.

HLA proteins can be placed on an inert surface medium as described above. Positioning can occur via binding, adhesion, anchoring, chemical reaction, or any other mode of attachment of HLA proteins to an inert surface medium. For example, the surface of the filter can be chemically designed to allow specific molecular and chemical properties to react with HLA proteins. For example, HLA proteins can be placed on an inert surface medium by covalent bonding, non-covalent interactions, or adsorption. Examples of non-covalent interactions include, but are not limited to, electrostatic interactions, van der Waals forces, π effects, and hydrophobic effects. In certain embodiments, HLA proteins may be bound to the surface of filters via analogues. As an example, HLA proteins may be placed on an inert surface via a maleimide analogue. In other embodiments, HLA proteins may be covalently attached to the surface of the filter via a maleimide analogue. In certain embodiments, HLA proteins may be introduced to the surface of the filter in an excess amount of solution to allow maximum saturation of the filter surface with HLA proteins. In certain embodiments, HLA proteins may be attached to the surface of the filter via thiol bonds, disulfide bonds, amine bonds, or any other suitable functional group attachment. Alternatively, HLA proteins may be covalently attached to the surface of the filter, eg, to cysteine residues.

Schematically depicted inert surface medium 402 of FIG. 4 includes HLA proteins 404 attached thereto. The attachment mechanism can be any mechanism, as previously described, while the inert medium can be any form to which HLA protein 404 can be bound, shown as beads in FIG. Often includes, but is not limited to, the configurations shown in Figures 2A-2D. Alternatively, inert surface media 402 may be fluid molecules and HLA proteins 404 may be disposed on the fluid molecules.

In some embodiments, the HLA proteins may be arranged on an inert surface such that the anchor positions of the HLA proteins are spaced from each other by at least the width of the HLA binding groove. This spacing allows T cells to bind HLA proteins. And if such spacing is maintained across the filter surface, the efficiency of the filter can be maximized. As an example, HLA protein 504 shown in FIG. 5 is attached to inert surface medium 502 via maleimide linker 506 . In this example, surface medium 502 comprises polysulfone 508 and poly(2-aminoethyl)acrylamide 510 .

In some embodiments, antigenic peptides can bind to HLA proteins on an inert surface medium. The term "peptide" generally refers to a short chain of amino acids (e.g., no more than 30 amino acids, 25 amino acids, 20 amino acids, or 15 amino acids) linked together by peptide bonds between two amino acids. amino acid). In some embodiments, peptides can be synthesized by standard procedures. In certain embodiments, peptides may be chemically synthesized by either manual or automated methods. Alternatively, peptides can be synthesized by fluorenylmethoxycarbonyl protecting group chemistry.

The term "antigenic peptide" or "immunogenic peptide" generally refers to the potential of a peptide to induce an immune response. Antigenicity or immunogenicity of a peptide can be measured by standard means. In some embodiments, antigenic peptides are loaded onto HLA proteins to form HLA-peptide complexes. By way of example, loading can occur via protein-peptide bonds. In particular, HLA proteins have peptide binding grooves that allow protein-peptide bonds to occur. The peptide-binding cleft is formed by two protein subunits, α1 and α2 in HLA I and a1-b1 in HLA II. Once the peptide binding groove is formed, the antigenic peptide can bind to the HLA protein through amino acid residue interactions between the peptide binding groove and the antigenic peptide. Exemplary interactions include hydrogen bonding, ionic interactions, hydrophobic interactions, and pi stacking. An antigenic peptide can bind to the HLA peptide binding groove to form an HLA-peptide complex.

In some embodiments, antigenic peptides can be associated with disease in patients and are loaded onto HLA proteins to form HLA-peptide complexes that can selectively bind to antigen-specific T cell receptors. can. For example, as described above, after loading, antigenic peptides can be recognized by T cells of an individual's immune system and initiate an attack on the T cells. In these examples, antigenic peptides complexed with HLA proteins can selectively bind to antigen-specific T-cell receptors.

In some embodiments, the antigenic peptide and HLA protein are selected to allow antigen-specific T cell receptors to bind to the antigenic peptide and HLA protein complex upon contact of the T cell with the complex. , thereby immobilizing specific T cells to the inert surface medium via the complex. T cells contact HLA-peptide complexes through spaces that allow interaction between the complexes and the desired T cells. Contact can occur through fluid flow, such as blood flow, or components of blood, such as plasma or specific blood cells. This recognition is based on the highly specific binding of only the desired T cells expressing specific T cell receptors that interact with specific HLA-peptide complexes.

The term "antigen-specific T cell receptor" generally refers to a receptor protein on the surface of T cells that binds to a specific antigen. T cells have specific T cell receptors on their surface, specific T cells bind to specific antigens, and other T cells do not bind to the same antigen, but to different antigens. This process is commonly referred to as selective binding. The relationship between T cells and receptors that recognize only specific antigens allows selective binding of T cells to antigen-specific receptors, binding only specific antigens. In some embodiments, HLA-peptide complexes disposed on an inert surface medium comprise antigenic peptides selected to bind to specific T-cell receptors. When antigen-specific T-cell receptors selectively bind and form complexes with HLA-peptide complexes, specific T-cells are anchored to the inert surface medium via the complexes.

In some embodiments, a disease-associated antigenic peptide can be a self peptide or a non-exogenous peptide specific to an individual. In certain embodiments, antigenic peptides may be made synthetically. Synthesis of antigenic peptides can be done manually or automatically. For example, antigenic peptides can be made synthetically using fluorenylmethoxycarbonyl protecting group (Fmoc) chemistry. Antigenic peptides can also be produced recombinantly. Recombinantly produced antigenic peptides may be similar to naturally occurring peptides or they may be modified. In certain embodiments, antigenic peptides may be produced recombinantly in-frame with HLA proteins. For example, the same plasmids used to recombinantly produce HLA proteins according to embodiments of the present invention can be used to recombinantly produce antigenic peptides.

In some embodiments, disease-associated antigenic peptides may include proteins specific for damaged tissues/organs in an individual. For example, such peptides can be derived from cells of the central nervous system. In certain examples, such peptides may include those that form part of the myelin sheath that surrounds axons in the central nervous system of an individual. Alternatively, disease-associated antigenic peptides may include proteins common to most or all cell types. By way of example, such peptides may include cytoplasmic, cytoskeletal, nuclear, or membrane proteins.

Antigenic peptides can be associated with various diseases. For example, antigenic peptides can be derived from proteins associated with multiple sclerosis. Such antigenic peptides include myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), myelin proteolipid protein (PLP), opaline protein, oligodendrocyte-specific protein (OSP), myelin-associated sugars. proteins (MAG), or combinations thereof. In certain embodiments, the antigenic peptide is MBP _87-99 , MBP _85-99 , MBP _83-96 , MBP _217-231, MBP _88-102, MBP _282-296, PLP _91-110, PLP _131-151, PLP _283-252, PLP _263-277, PLP _58-72, PLP _13-27, OPALIN _46-60, OPALIN _27-41, OPALIN _127-141, MOG _210-224, MOG _29-43, MOG _176-190, MOG _225-239, OSP _74-88 , OSP _114-128, MAG _8-22, MAG _467-481, MAG _529-543 , or combinations thereof.

Disease-associated antigenic peptides can be identified or analyzed by standard methods. In some embodiments, identified peptides can be quantified. Alternatively, the amino acid sequence of such peptides may be identified. Such peptides can be compared to a database of antigens to derive relevant information about the peptide. For example, the binding affinity of a peptide for a particular HLA can be measured. Accordingly, identifying or analyzing an antigenic peptide can involve comparing the peptide to a database of disease-associated antigenic peptides that contain peptide binding affinities to HLA complexes. In certain embodiments, peptide identification or analysis may comprise examining peptides isolated from HLA complexes taken from tissues of the diseased individual. For example, peptides from the cerebrospinal fluid of affected individuals can be tested. Alternatively, or additionally, tissue from an affected individual may be harvested. A population of HLA complexes with linked or loaded peptides can be isolated from the cells of the diseased individual. Peptides can then be separated from the HLA complex, eg, by chemical means. The isolated peptides can then be sequenced and analyzed for frequency in order to associate them with the individual's particular disease. Using these mechanisms, filters can be personalized to treat specific individual ailments, as described above.
A biological filter for cytoreduction of multiple sclerosis-associated T cells

Consistent with the disclosed embodiments, the biological filters described above can be used for cytoreduction of specific cells. For example, filters can be used for cytoreduction of pathogenic or non-pathogenic cells. As used herein, the term "cell reduction" generally refers to a procedure in which certain cells, or groups of cells, are removed from a composition, thus reducing their relative percentage in the total population of cells. point to This excision is based on the specific recognition of unique cell subsets, in other words, specific clonality rather than applying standard techniques that cannot discriminate between different cells with different biological or physical properties. is achieved by cytoreduction of In some embodiments the cells comprise T cells. For example, a filter can be configured to remove pathogenic T cells associated with disease or associated with recognition of specific structures of proteins or peptides. In certain embodiments, biological filters can be used for cytoreduction of multiple sclerosis-associated T cells.

The disclosed filters can be used on patients. As used herein, the term "patient" may refer to a subject with a disease or other affliction. A patient can be a human or any other mammal. In some embodiments, methods of depleting specific T cells are contemplated. The term "specific T cells" refers to a population of T cells that express a particular T cell antigen receptor, a specific clone of T cells. A T cell population that expresses a particular T cell antigen can be targeted for removal, for example, if the population is identified as causing or otherwise affecting patient distress. In other embodiments, the specific T cells may comprise multiple T cell populations, wherein each population expresses a different T cell antigen receptor, and the different T cell antigen receptor expressing populations are Can be targeted for removal.

In some embodiments, T cells that do not express the particular T cell antigen receptor or targeted receptor cannot be ablated. As understood by the inventors, the term "T cells" can include any type of lymphocyte that develops in the thymus and plays a central role in the immune response. In some embodiments, the specific T cells are one or more of helper CD4+ T cells, cytotoxic CD8+ T cells, naive T cells, memory T cells, regulatory CD4+ T cells, natural killer T cells, mucosa-associated T cells. It may contain invariant T cells and/or γδ T cells. Alternatively, or in addition, specific T cells may comprise at least one of CD4+ cells or CD8+ cells.

Target T cells may be pathogenic or non-pathogenic. Pathogenic T cells may play a similar role as nonpathogenic T cells, but pathogenic T cells can recognize self-structures and substances and attack them. The term "pathogenic" is defined above. By targeting and eliminating pathogenic cells, the patient's disease may be alleviated. Nonpathogenic T cells are targeted for elimination, for example, if a particular lineage is expected to evolve to the point that current nonpathogenic T cells may become pathogenic in the future. good too. Thus, active elimination of non-pathogenic cells may prevent later manifestations of disease.

Pathogenic cells may be associated with any one or any combination of the above autoimmune diseases. In certain embodiments, the pathogenic cell is multiple sclerosis (MS), lupus, celiac disease, Sjögren's syndrome, polymyalgia rheumatoid arthritis, scleroderma, ankylosing spondylitis, type 1 diabetes, alopecia areata, Vasculitis, autoimmune hepatitis, autoimmune lymphoproliferative syndrome (ALPS), autoinflammatory disease, Goodpasture syndrome, Lambert-Eaton syndrome, antiphospholipid syndrome (APS), neuromyelitis optica (NMO), paraneoplastic syndrome , primary cholangitis, stiff-person syndrome (SPS), antiphospholipid antibody syndrome (APS), or temporal arteritis. In certain embodiments, the autoimmune disease is multiple sclerosis.

Several studies have shown that the adaptive immune system is strongly involved in the molecular pathogenesis of multiple sclerosis. As shown in Figure 6, autoantigens derived from central nervous system proteins such as myelin trigger activation of the immune system, allowing cells such as T cells, B cells, and macrophages to cross the blood-brain barrier and infiltrate, leading to inflammation, It causes demyelination, gliosis, and neuroaxonal degeneration. Currently, there is no treatment that can cure this disease.

Embodiments of filters can include a media host material that selectively binds to antigen-specific T cell receptors. As noted above, the term "vehicle" can include any substance that can serve as a base, support, or anchor for substances that selectively bind to cells. Since the binding material is immobilized on the medium, when the cells bind to the binding material, the cells are effectively trapped on the medium to which the binding material is immobilized. Substances that selectively bind cells can vary depending on the intended use of the filter. By way of example, the binding material on the medium can be configured to entrap cells, proteins, nucleic acids, lipids, polysaccharides, or any other biological substance. Details of the medium are discussed in other paragraphs herein and are not repeated to avoid duplication. As used herein, "selective binding" refers to any biological or chemical process by which a target is selectively bound such that it is removed from the environment in which the target is located. In a broad sense, binding includes any process of combination, adhesion, coupling, or reaction that causes target cell removal.

Many types of surface media can be used including solids, semi-solids or fluids. When solid or semi-solid, the medium can have any form. Examples provided in Figures 2A-2D include sheet materials, fibers, beads, and sponge-like materials. Other examples include mesh structures, liquids and gels. Likewise, the composition of the media may vary depending on the intended use. By way of example only, media can include inert, non-synthetic, synthetic, polymeric, high performance thermoplastics, polysulfone, polysulfone derivatives, glass matrix, silicon matrix, polydimethylsiloxane (PDMS), polycarbonate, polyetherimide (Ultem), tritane. , polyelectrolyte, polyacrylic acid, or poly(2-aminoethyl)acrylamide in one or more ways. Alternatively or additionally, the medium may be polyacrylic acid present at about 5-40 weight percent; polysulfone present at about 60-95 weight percent; polystyrene, polyethylene glycol (PEG) or PEG derivatives, capable of intermolecular cross-linking PEG density is maximized by creating a six-armed star molecule of PEG, and/or avidin, streptavidin, or any form thereof. Again, these are merely examples and should not be considered limiting of the present disclosure in its broadest sense.

Schematically, Figures 7A-7D show non-limiting examples of media consistent with embodiments of the present disclosure. FIG. 7A shows the PDMS material. FIG. 7B shows a polycarbonate material. FIG. 7C shows the Ultem material. FIG. 7D shows the Tritane material.

The medium can host a binding material that selectively binds to and captures biological material such as cells. For example, the cells may be pathogenic T cells and may adhere to the medium in any manner, including through covalent bonds, non-covalent interactions or adsorption. Non-covalent interactions include hydrogen bonding, ionic interactions, hydrophobic interactions, or pi stacking. In certain embodiments, binding materials may include proteins. For example, in some embodiments a protein may include an antibody. In certain embodiments, proteins may comprise human leukocyte antigens (HLA). Although the binding material may selectively bind only to specific cells, the binding material may first bind to the host medium. Thus, use of the phrase "selectively binds only to specific cells" refers to the selective binding of a cell (or other biological substance) trapping process, which may occur through binding to the host. It is not the mechanism that connects the medium to the binding material.

In some embodiments, the selectively binding host material comprises HLA. HLA can bind to peptides to form HLA-peptide complexes. HLA-peptide complexes can recognize specific epitopes on biological material (eg, T cells). In certain embodiments, HLA-bound peptides may be derived from proteins involved in disease. In one example, the binding material comprises an HLA-myelin-peptide complex selected to bind to a myelin-specific T-cell receptor, thereby recognizing the HLA-myelin-peptide complex. allows specific binding of The HLA-myelin-peptide complexes can be placed on the media filter in any manner, including through covalent bonds, non-covalent interactions or adsorption. As used herein, the term "positioning" can generally refer to a process by which a selected protein can attach to a desired surface via chemical reaction (or other mechanism). . A surface can be chemically engineered to impart specific molecular and chemical properties in order for it to react with proteins. This arrangement can occur when the surface is introduced into a solution containing the protein of interest, preferably in excess to allow maximum saturation of the surface with the protein.

By way of example, if the medium may contain avidin, streptavidin or any variant thereof, the capture material may be linked to biotin that can interact with avidin, streptavidin or variants thereof on the surface of the medium. , thereby fixing the capture material to the medium. In another example, the medium may contain free carboxyl groups, amine groups, maleimide groups, or any other functional groups that can interact with functional groups on the capture material, thereby immobilizing the capture material to the medium. . In yet another embodiment, the medium comprises a blend of polysulfone and polyacrylic acid, and the capture material is a protein that binds to the medium via the carboxyl groups of the polyacrylic acid. Additionally, mixtures of polysulfone and polyacrylic acid can be modified to contain amine groups, and proteins can bind to media via reaction with the amine groups. In a further example, a blend of polysulfone and polyacrylic acid can be modified to include maleic acid, maleimide groups, or analogs thereof. Maleic acid, maleimide groups or analogues thereof can be extended with a carbohydrate linker. The capture material may bind to the medium through reaction with maleic acid, maleimide groups or analogues thereof. In certain embodiments, the HLA-peptide complex is positioned on the medium via maleic acid, maleimide or a maleimide analogue.

Schematically, FIG. 8 shows medium 802 containing HLA-myelin-peptide complexes 804 that recognize T cell receptors on T cell population 806 . The medium 802 is shown in sheet form and may be in any form including, but not limited to, the forms shown in FIGS. 2A-2D.

As noted above, the term "human leukocyte antigen" (HLA) generally refers to a system or complex of proteins encoded by an individual's major histocompatibility (MHC) gene complex. Three HLA proteins have been discovered in humans. They are HLA I, HLA II, HLA III. These three HLA proteins differ in many ways, including structurally, expression patterns, and target recognition. As used herein, the term "HLA I" generally consists of α and β2-microglobulin chains, is expressed in all nucleated cells, and interacts with CD8+ T cells in vivo. Refers to the HLA class that As used herein, the term "HLA II" generally refers to the HLA class that is composed of α and β chains, is expressed in antigen presenting cells, and interacts with CD4+ T cells in vivo. Point. HLA proteins are typically found on the surface of human cells, involved in the regulation of an individual's immune system. For example, HLA proteins can function by recognizing foreign, non-self materials within an individual and initiating an immune response that neutralizes those materials. Foreign, non-self material can be incorporated into HLA complexes and presented to the individual's immune system in order to initiate or stimulate the individual's immune response. Each individual has a specific set, or type, of HLA proteins. In some embodiments, an individual's HLA type can be identified using standard laboratory techniques in an accredited clinical laboratory. For example, identifying an individual's HLA typing can include analyzing a blood sample taken from the individual. Alternatively, an individual's HLA type may be identified by other suitable means. As used herein, the term "HLA typing" generally refers to the process by which an organism's HLA set is determined. For example, HLA typing can be performed via DNA sequencing, microlymphocyte toxicity assays, or DNA hybridization to oligonucleotide probes that identify one or more HLA types of the patient. For example, HLA typing can include testing for antibodies that target specific HLA proteins. Some methods for HLA typing use DNA-based methods to define HLA alleles and allele groups. Different DNA-based molecular techniques can be used depending on the clinical application. Some HLA typing procedures may include reverse SSO (rSSO) or SBT (Sequence Based Typing). Any technique that can be used to identify HLA types is within the scope of this disclosure. Many clinical laboratories perform HLA typing services, and identifying an HLA type within the meaning of this disclosure involves either performing a typing procedure or sending a bodily fluid sample to a laboratory that performs the procedure and returns results. can include In some embodiments, the capture material may comprise HLA proteins and may further comprise peptides to form HLA-peptide complexes. HLA-peptide complexes can be placed on the medium via, for example, maleic acid, maleimide or analogues thereof. In some embodiments, HLA-peptide complexes can recognize T cell receptors on specific T cell populations and thereby trap T cells on the media. In other embodiments, multiple different HLA-peptide complexes may each recognize different T cell receptors or different T cell clones on multiple different T cell populations.

The term "T cell receptor" (TCR) generally refers to a protein complex found on the surface of T cells. Genetically modified TCRs exhibit remarkable diversity, with each type of T-cell receptor recognizing specific antigenic peptides bound to HLA, thereby signaling to activate other components of the immune system in vivo. Start a cascade.

In some embodiments, immunogenic peptides may be associated with various diseases, including, for example, autoimmune diseases. Disease-associated immunogenic peptides can be identified or analyzed by standard methods, as described above. In some embodiments, autoimmune disease refers to multiple sclerosis. For example, immunogenic peptides include myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), myelin proteolipid protein (PLP), opaline protein, oligodendrocyte-specific protein (OSP), myelin-associated It may be derived from myelin proteins including, but not limited to, glycoprotein (MAG), or combinations thereof. As noted above, exemplary embodiments of immunogenic peptides are MBP _87-99 , MBP _85-99 , MBP _83-96 , MBP _217-231, MBP _88-102, MBP _282-296, PLP _{91-110 ,} PLP _131-151, PLP _283-252, PLP _263-277, PLP _58-72, PLP _13-27, OPALIN _46-60, OPALIN _27-41, OPALIN _127-141, MOG _210-224, MOG _{29-43 ,} MOG _176-190, MOG _225-239, OSP _74-88 , OSP _114-128, MAG _8-22, MAG _467-481, MAG _529-543 , or any combination thereof. Alternatively or additionally, other myelin-associated proteins, including but not limited to myelin-associated glycoprotein (MAG), oligodendrocyte-specific protein (OSP) and myelin-associated oligodendrocyte basic protein (MOBP) HLA protein and peptide complexes derived from HLA can also be utilized. Also contemplated in some embodiments are HLA proteins complexed with peptides derived from multiple sclerosis-associated non-myelin proteins. By way of example, such antigenic peptides are derived from aquaporin channel protein, αB-crystallin, transaldolase-H, S-100 (105), and 2',3'-cyclic nucleotide-3'-phosphodiesterase (CNPase). can be

In some embodiments, the HLA proteins in the HLA-peptide complex can identify the HLA type to match the patient. As noted above, HLA typing can be performed using methods including, but not limited to, DNA sequencing, microlymphocyte toxicity assays, or hybridization of DNA to oligonucleotide probes. For example, genomic DNA can be purified from an organism, amplified using the polymerase chain reaction (PCR), and then sequenced to identify the HLA type of the organism. In another example, genomic DNA can be purified from an individual, amplified using PCR, and hybridized with sequence-specific probes. In some embodiments, sequence-specific probes may be conjugated to fluorochromes to allow detection of double strands using chemiluminescence. In some embodiments, the HLA type of an individual organism is identified and HLA proteins of the same type are recombinantly produced for use in biological filters.

Antigenic peptides form complexes with HLA proteins through the peptide-binding grooves of HLA proteins. As used herein, the term "peptide binding groove" generally refers to a region within an HLA protein that facilitates binding of antigenic peptides. Antigenic peptides of various lengths can bind to HLA proteins. By way of example, an antigenic peptide may contain 8-10 amino acids or 13-18 amino acids.

Schematically, FIG. 9 shows HLA I and HLA II proteins bound to myelin-derived antigen peptides, where myelin-derived antigen peptide 902 is shown adjacent to HLA peptide binding groove 904. FIG.

In some embodiments, the HLA-peptide complex can be recombinantly designed or obtained endogenously from an individual such as a patient. In some embodiments, HLA proteins include HLA I and/or HLA II. By way of example, the HLA proteins of the HLA-peptide complex can be further modified either genetically or in vitro. For example, HLA proteins can be cleaved to produce a C-terminal cysteine. The HLA-peptide complexes can react with maleimide or its analogues on the medium, thereby immobilizing the HLA-peptide complexes on the medium. In a preferred embodiment, the HLA-peptide complexes are arranged on the filter medium such that the anchor positions of the complexes are spaced from each other by at least the width of the HLA binding groove.

In certain embodiments, the filter can include multiple layers configured to allow fluid flow therebetween, as described above and with reference to FIGS. 2A-2D.
Portions of adjacent layers may contact each other or may be separated from each other by scaffolding, eg, as described above and shown in FIG.
A device for removing pathogenic T cells from a patient's blood

Some embodiments of the present disclosure may include devices for removing pathogenic T cells from a patient's blood, such as devices incorporating one or more biological filters as described above. The device may be set up in a medical facility such as an outpatient clinic, similar in that it is in a kidney dialysis center where patients can receive regular extracorporeal blood treatment. In order to effectively treat patients, these outpatient clinics may be equipped with devices capable of depleting specific pathogenic T cells. This procedure may be performed, for example, using equipment that implements a two-step process. Accordingly, consistent with this disclosure, various devices may be provided for removing pathogenic T cells from a patient's blood. As noted above, pathogenic T cells may be correlated with certain diseases. For example, a "pathogenic T cell" can be a cell that causes a disease, disorder, or other abnormal medical condition such as autoimmune disease, cancer, and post-transplant complications. The filters used in the device can be designed to trap these specific pathogenic T cells and remove them from the blood, thereby alleviating disease symptoms.

By way of non-limiting example, FIG. 10 is a schematic diagram of an apparatus 1000 for removing pathogenic T cells from a patient's blood supplied by inlet conduit 1028. As shown in FIG. The inlet conduit 1028 may be directly connected to the patient via the patient's needle or shunt. Alternatively, inlet conduit 1028 may be connected to a blood reservoir. The device can have various configurations depending on the intended use and specific functional requirements.

According to some embodiments, such devices may include a first stage area configured to hold a blood separation device capable of separating white blood cells from other fractions of whole blood, The blood separation device has an inlet, a leukocyte outlet, and a blood fraction outlet configured to allow return of other fractions into the patient. As used herein, the term "first stage region" refers to the separation of one or more fractions of blood from at least another fraction of blood, and more specifically to the separation of leukocytes from whole blood. Refers to the part of the apparatus associated with separation from other fractions. Separation may be accomplished via a blood separation device using any mechanical, chemical or other means of achieving separation of blood components. That is, the separation device is not limited to any particular principle as long as it can separate white blood cells for subsequent filtration.

In one embodiment, the blood separation device can be configured to facilitate apheresis or other centrifugal functions to mechanically separate blood into at least two portions. Accordingly, the first stage may include components related to rotation of the blood container. These components may include a rotating assembly driven by a motor and a mechanical structure for gripping the blood container. The blood container itself may be part of a disposable tubing set.

The inlet of the blood separator can be the location where blood enters the stage. For example, it may be located within an area or structure configured to hold or house disposable tubes for supplying whole blood to the first stage. Similarly, the leukocyte outlet and the blood fraction outlet are each located within a region or structure configured to hold or house a disposable tube for separately conveying leukocytes and other blood fractions from the first region. may be As described in more detail below, white blood cells (or the fraction thereof containing T cells) proceed to filtration, while other blood fractions, either directly or via intermediate collection chambers, return to the patient. can be specified as Although the first stage is described above in relation to disposable tubing sets, in some configurations the conduits and/or separators need not be disposable.

The exemplary apparatus 1000 of FIG. 10 includes a first stage area 1002, a blood separation apparatus 1004 comprising:
It may have an inlet region 1006 , a blood cell outlet region 1008 and a blood fraction outlet region 1010 . When a disposable tubing set is used, the upstream portion of blood fraction outlet conduit 1012 passes through blood fraction outlet section 1010 to direct the blood fraction (excluding white blood cells) through Y junctions 1037 to 1039 outlets. It may be returned to the patient's body. This can be done via a fluid connection to the patient's vasculature or by first storing the blood in a chamber before returning to the patient. Similarly, the upstream end of leukocyte conduit 1023 may pass through leukocyte exit region 1008 to the filtration stage.

As an example, blood separation device 1004 may be configured to separate blood using apheresis, centrifugation, or filtration. In other words, the blood separation device may be an apheresis system, a centrifugation system, or a filtration system, examples of each of which are shown in Figures 11A-11C. In the exemplary apheresis system 1100A shown in FIG. 11, whole blood enters the rotating vessel 1112 via inlet conduit 1102 and may be stratified into plasma 1104, white blood cells 1106, and red blood cells 1108. Leukocytes 1106 may then be extracted via outlet conduit 1110 connectable to leukocyte outlet 1008 in FIG.

In the exemplary centrifugation system 1100B shown in FIG. 11B, centrifugal force is used to separate the components of whole blood 1112 into plasma 1114, red blood cells 1116, and white blood cells and platelets 1118, similar to previous apheresis system embodiments. added to. The exemplary filtration system 1100C shown in FIG. 11C includes multiple cell-trapping structures 1124 and multiple filters 1128 that separate whole blood cells 1122 and plasma 1126 together.

Consistent with some embodiments, a first pump may be provided to move blood from the patient through the first stage area. A first pump may be positioned upstream of the inlet region of the first stage for pumping blood into the first stage region. Alternatively, a first pump may be positioned downstream of the first stage to force blood into the first stage through negative pressure. Any form of pump may be used, but in a preferred embodiment the pump may be a peristaltic pump. By way of example, a peristaltic pump 1021 may be provided as shown in FIG. 10 to transport blood from inlet conduit 1028 to first stage 1002 .

Consistent with disclosed embodiments, configured to retain a biological filter comprising a human leukocyte antigen (HLA)-peptide complex, the one or more filter inlet regions and the one or more filter outlet regions are wherein the first stage area and the second stage area are oriented to allow flow from the leukocyte exit area of the blood separation device to one or more inlets of the biological filter second stage area. can provide a second stage region. As used herein, the term "second stage area" refers to the portion of the apparatus associated with filtration. For example, the second stage area may be an area of the device configured to hold a biological filter. Biological filters comprising human leukocyte antigen (HLA)-peptide complexes are described in more detail herein and are therefore not repeated in the discussion of this embodiment. A filter retained in the second stage region has an inlet in fluid communication with the leukocyte outlet of the first stage. Since T-cells are contained in the leukocyte fraction, this configuration can maximize filter effectiveness and can be used in other compartments when other fractions are known not to contain targets for filtration. Eliminates the need to introduce minute blood into the filter. The non-leukocyte fraction can enter the filter and if this happens the system will still work, but with lower efficiency.

As an example, FIG. 10 shows a second biological filter 1016 configured to hold a human leukocyte antigen (HLA)-peptide complex and having one or more inlets 1018 and one or more outlets 1020. A staging area 1014 is shown. First stage region 1002 and second stage region 1014 are oriented to allow flow from leukocyte outlet 1008 of blood separation device 1004 to inlet 1018 of biological filter 1016 . All embodiments of biological filters and HLA-peptide complexes as described herein are suitable for use in the second stage area 1014. The same principles described herein for the filtration of T cells can be applied to the filtration of other biological substances and are considered within the scope of this disclosure.

In one embodiment, the biological filter can include multiple layers, such as the layers of FIG. 3, and other embodiments of multilayer biological filters described herein, such as FIGS. 2A-2D. Each layer of a biological filter may contain a human leukocyte antigen (HLA)-peptide complex thereon, and the more surface area exposed to the complex, the more efficient the filter. In one embodiment, the biological filter 1016 can be configured to selectively bind pathogenic T cells, such as disease-specific pathogenic T cells. By "selectively binds" is meant that a peptide must bind to an HLA protein in order for a specific T cell with a specific T cell receptor to identify its target peptide (epitope). . For example, biological filter 1016 may include a human leukocyte antigen (HLA)-peptide complex, where the peptides in the complex are antigenic peptides that may be associated with various diseases, such as multiple sclerosis. Antigenic peptides associated with multiple sclerosis can be derived from the exemplary proteins described above. Examples of antigenic peptides have been previously described.

Consistent with the disclosed embodiments, a second pump may be provided for recirculating leukocytes from one or more outlets of the biological filter to one or more inlets of the biological filter. The function of the second pump is to provide white blood cells with the ability to pass through the biological filter 1016 multiple times. With each pass, more pathogenic T cells bind to the filter. Recirculation may continue for a sufficient time to remove enough pathogenic T cells to achieve the design specifications of the system, which in itself will depend on the type of filter and treatment parameters for the particular patient. can depend.

As an example, the apparatus 1000 of FIG. 10 may include a second pump 1022 for recirculating white blood cells from the biological filter outlet 1020 to the biological filter inlet 1018 . As with first pump 1021, second pump 1022 may be a peristaltic pump. To enable recirculation, electronically controllable valves 1027 and 1029 may isolate filter 1016 such that actuation of pump 1022 causes recirculation. Values 1027 and 1029 may be adjusted by controller 1030, as described below.

In certain embodiments, the second stage area 1014 is sized such that the biological filter 1016 can contain about 3-50 ml of white blood cell fraction. The apparatus of Figure 10 can process blood in batches. After a batch of leukocytes has passed from stage 1 to stage 2, flow may be restricted to stage 2 until batch processing in stage 2 is complete, as described below.

Consistent with disclosed embodiments, a plurality of electronically controllable valves may be provided for directing blood through the first stage area and the second stage area. An electronically controllable valve may include any device that regulates fluid flow in response to an electrical signal. Accordingly, a "plurality of electrically controllable valves" respectively regulate the flow of a patient's whole blood, white blood cells, non-pathogenic white blood cells, and/or other fractions of whole blood (i.e., plasma, red blood cells). Two or more electrically controllable valves that regulate, direct or control. For example, one or more valves may be used to prevent additional white blood cells from entering the filter while the biological filter 1016 is performing its work. In all embodiments, recirculation through a biological filter is not required, but if recirculation is used, a valve may be used to isolate the filter and allow leukocytes to recirculate.

Referring to the example of FIG. 10, device 1000 may include valves 1027 and 1029 as previously described. Similarly, peristaltic pump 1021 can effectively function as a valve when stopped.

The disclosed embodiments may include one or more processors. "One or more processors" may constitute any physical device or group of devices having electrical circuitry that performs logical operations on one or more inputs. For example, one or more processors may be application specific integrated circuits (ASICs), microchips, microcontrollers, microprocessors, central processing units (CPUs) in whole or in part, graphics processing units (GPUs), digital signal processors. (DSP), Field Programmable Gate Array (FPGA), Server, Virtual Server, or any other circuit suitable for executing instructions or performing logic operations. . Instructions to be executed by one or more processors may be preloaded, for example, in a memory integrated with or embedded in the controller, or may be stored in separate memory. Memory may be random access memory (RAM), read-only memory (ROM), hard disk, optical disk, magnetic media, flash memory, other permanent memory, fixed memory, volatile memory, or any other memory capable of storing instructions. mechanism. In some embodiments, one or more processors may include two or more processors. Each processor may have a similar structure, or the processors may have different structures that are electrically connected or disconnected from each other. For example, the processors may be separate circuits or integrated into a single circuit. Where multiple processors are used, the processors may be configured to operate independently or in concert. Processors may be coupled electrically, magnetically, optically, acoustically, mechanically, or by any other means that allow them to interact. An example processor 1030 is shown in FIG. Although schematically illustrated as a single block, processor 1030 may comprise a single processor or multiple processors commonly located or spread across multiple locations within device 1000 . Moreover, some or all processing functions may be performed remotely from device 1000, such as at locations accessible via a communications network.

Consistent with some embodiments, the one or more processors direct blood flow through the first stage region until a certain amount of white blood cells are separated and transported to the second stage region. It may be configured to control the pump. The one or more processors may be configured to control components such as pumps and valves by sending electronic signals to the pumps and valves. These signals may be sent by one or more processors to adapt the device to a treatment protocol. For example, the one or more processors send an activation signal to the pump to allow blood to be sent to a first stage for separation and separated white blood cells to be flowed to a second stage for filtration. You may

As an example, the processor 1030 shown in FIG. 10 controls the first stage 1002 so that blood flows through the first stage area 1002 until a certain amount of white blood cells are separated and transported to the second stage area 1014. It may be configured to control pump 1021 . Processor 1030 may also control blood separation device 1004 to cause separation. For example, if blood separation device 1004 is associated with a motor (not shown) for rotating the centrifuge chamber or compartment, processor 1030 can control the motor. Once blood is separated, leukocytes can exit leukocyte exit region 1008 and enter biological filter 1016 via conduit 1023 . An electronically controllable valve 1027 may be placed in the pathway of conduit 1023 to regulate leukocyte efflux to second stage region 1014 . The force of pump 1021 can cause white blood cells to flow through white blood cell conduit 1023 . Alternatively or additionally, another pump (not shown) may be placed within the leukocyte conduit 1023 to facilitate the flow of leukocytes to the second stage region 1014 .

In some disclosed embodiments, the one or more processors may be configured to stop the first pump when the white blood cell mass is separated and transported to the second stage area. Shutting down the first pump can be used when the filtration capacity of the second stage biological filter is limited. Thus, biological filtration may be performed in batches in which no additional new leukocytes are introduced into the biological filter during the filtration of any given batch. To accomplish this, once the biological filter in the second stage reaches capacity, the processor may stop the pump (or close the valve) that supplies additional white blood cells to the biological filter. . This can also be done by closing the valve on the inlet side of the biological filter to prevent additional white blood cells from entering the filter. The processor may limit the amount of white blood cells entering the biological filter based on a program executed by the processor. The program may, for example, rely on feedback from systems such as flow sensors or volume sensors. For example, a flow sensor may determine whether the volume of white blood cells passing to the second stage is within target parameters of the filter. Alternatively, a first stage or second stage volume sensor may detect when the volume of separated white blood cells reaches a target parameter.

In some other variations, the pump feeding the first stage may continue to operate with the blood separation device even after the capacity of the biological filter in the second stage area is reached. In such variations, the pump may continue to run to prepare the next batch of white blood cells for feeding the biological filter. Therefore, the stoppage of the pump need not occur at the same time as the start of batch filtration in the second stage. Additionally, a buffer reservoir for leukocytes (not shown) may hold the separated leukocytes ready for filtration. The second stage may be supplied by leukocytes via a buffer reservoir. At some point, simultaneously with the start of filtration of a new batch, while the batch is being filtered, or during the last batch of filtration, the pump feeding the first stage will turn on the filter while filtration in the second stage is in progress. may be stopped by one or more processors.

As an example, the processor 1030 shown in FIG. 10 performs a first step after the amount of white blood cells separated by the blood separation device 1004 has matched the capacity of the biological filter 1016, or after matching the operating parameters of the system. of the pump 1021 may be stopped. This may be detected, for example, by sensor 1033 associated with first stage 1002 . Sensor 1033 may detect the volume of collected white blood cells (or related fraction thereof) within blood separation device 1004 or the amount of white blood cells exiting blood separation device 1004 . Further leukocyte flow to the biological filter 1016 may be restricted if the amount meets system parameters. As mentioned above, the pump 1021 may continue to run for at least some time while filtration in the second stage 1014 occurs simultaneously. If pump 1021 continues to operate during filtration, processor 1030 may be programmed to close valve 1027 to prevent white blood cells from entering biological filter 1016 .

In some embodiments, the one or more processors operate the second pump and control the plurality of valves for a period of time sufficient to separate pathogenic T cells from non-pathogenic white blood cells. It may be configured to recirculate the amount of leukocytes through the target filter. In particular, if the system is designed for use with a filter that requires multiple leukocyte passages, a bypass loop is provided to recirculate leukocytes through the filter in order to remove sufficient amounts of pathogenic T cells. can be made This can be accomplished by placing valves on either side of the second stage and placing a pump in the bypass loop to circulate the leukocytes from the outlet of the biological filter to the inlet of the biological filter. A valve as used herein may be a conventional valve or any structure that prevents flow. In some cases, if the flow through the non-actuated pump is restricted, the non-actuated pump can be considered a valve for this purpose. One or more processors may be programmed to close the valve surrounding the biological filter and run the recirculation pump for a period of time consistent with a particular use case or design parameters. For example, recirculation time may be a function of filter size/capacity, desired filtration rate, and filter condition. For example, as the filter ages, more recirculation may be required to achieve desired goals. The processor may track the amount of leukocytes already filtered or the time the filter has been used, increasing recirculation time as a function of either these parameters or any other parameter indicative of filter health. may

As shown in the example of FIG. 10, processor 1030 may be configured to control valves 1027 and 1029 upstream and downstream of biological filter 1016, respectively. When both of these valves are closed and pump 1022 is activated by processor 1030, white blood cells recirculate through biological filter 1016. FIG. If valve 1029 is omitted, pump 1031 may be considered a valve because it blocks the flow path. Similarly, valve 1027 may be replaced with a pump that configures the valve when the pump is turned off.

The one or more processors may also be configured to return non-pathogenic white blood cells to the patient. This can be accomplished directly by transferring the biological filter to a tubing set connected to the patient's arteriovenous system, or indirectly by feeding the filtered leukocytes into a container from which the leukocytes are extracted. may later be returned to the patient.

Return of non-pathogenic leukocytes may be performed using the apparatus of FIG. 10, as an example. After following a recirculation program implemented by processor 1030 , valve 1029 may be opened and pump 1031 may be activated to remove filtered white blood cells from biological filter 1016 . Pump 1031 may be a peristaltic pump that returns treated leukocytes to the patient via treated leukocyte conduit 1035 . To minimize the number of skin puncture needles or other cannulas required, Y-junction 1037 is used to separate the blood fraction carried by blood fraction outlet conduit 1012 and the filtered blood fraction carried by conduit 1035 . Both white blood cells may be returned to the patient via a single vein.

Disclosed embodiments are designed to prevent leukocytes from returning to the patient while the second pump is activated to recirculate the amount of leukocytes through the second stage biological filter. It may include one or more valves controllable by the above processor. Any valve or other structure that acts as a valve may be used to prevent leukocytes from returning to the patient during recirculation. As an example, valve 1029 may be closed by controller 1030 to prevent leukocytes from returning to the patient during recirculation of leukocytes through biological filter 1016 .

In some embodiments, a second pump is activated to move white blood cells from the first stage area to the second stage area while recirculating the amount of white blood cells through the second stage biological filter. One or more valves controllable by one or more processors may be included to prevent this. As previously mentioned, if a batch of leukocytes is to be filtered in a second stage, it may be preferable to restrict further influx of leukocytes into the biological filter 1016. This is particularly preferred when the biological filter is already at its volumetric capacity. Any structure that restricts flow to the second stage region may be considered a valve. As an example, valve 1027 in leukocyte duct 1023 is one such structure that, when closed by processor 1030, prevents leukocytes from migrating to the second stage region. Similarly, a pump (not shown) in the path of leukocyte conduit 1023 may also act as a valve when stopped by processor 1030 .

Further, according to some embodiments of the present disclosure, the one or more processors control the plurality of electrically controllable valves to batch process the leukocytes in the second stage region and One batch is recirculated in the second stage area and then returned to the patient before the one or more processors allow the second batch of leukocytes to enter the second stage biological filter. may be configured. As noted above, this batching process may be advantageous when using filters that are unable to adequately remove pathogenic T cells in a single pass through the filter. By including a bypass from the outlet of the filter to the inlet of the filter, leukocytes can pass through the filter multiple times, increasing the clearance of pathogenic T cells. This can be readily accomplished by controller 1030, which in the example of FIG. 10 is configured to close valves 1027 and 1029 and activate recirculation pump 1022 during the recirculation process. Following sufficient recirculation, it may be timed by processor 1030 to open valve 1029 and activate pump 1031 to return the batch of filtered white blood cells to the patient. Processor 1030 then opens valve 1027 and activates either pump 1021 or another pump (not shown) within the pathway of leukocyte conduit 1023 to introduce additional leukocyte cells into second stage region 1014. You may Before the batch is discharged from the second stage, the processor 1030 can predict the need for further white blood cell separation, and after the biological filter 1016 has been discharged from the previous batch of white blood cells, the separated white blood cells are Mechanisms associated with pump 1021 and blood separation device 1004 may be enabled so that they are ready for transfer to biological filter 1016 . In some embodiments, the one or more processors are configured to control one or more valves to add red blood cells and saline prior to returning other fractions of whole blood to the patient. obtain. This can occur via connection of the device to one or more reservoirs (not shown) for supplying red blood cells and/or saline to the blood compartment. For example, in Figure 10, a controllable valve may be included in the path of the fractionated blood outlet conduit 1012, which may be connected to one or more reservoirs (not shown). A controller 1030 was added to introduce red blood cells and/or saline into the fractionated blood outlet conduit 1012 (or some other location) for delivery to the patient along with the returning whole blood fraction. Valves may be adjusted.

Similarly, one or more processors may be configured to control one or more valves to deliver anticoagulant to the second stage region. Anticoagulants are beneficial in preventing thrombus formation during the recirculation process. As an example, an anticoagulant reservoir (not shown) may be placed in flow connection with conduit 1023 or 1024 with a metering valve (not shown) controlled by processor 1030 .

Some disclosed embodiments may further include a blood mixing device, wherein the one or more processors extract other fractions of whole blood and/or non-pathogenic white blood cells prior to return to the patient. configured to control the blood mixing device to mix; Examples of blood mixing devices include mixers such as vortex mixers that gently shake or agitate other fractions of whole blood and/or non-pathogenic white blood cells without disrupting the components or cells contained therein. mentioned. Such a device may be included downstream of the Y-junction 1037, or in place of the Y-junction 1037 in the example of FIG. In yet another example, the disclosed embodiments can include an arterial pressure control unit (not shown). Such devices can be used to ensure proper regulation of blood pressure when blood or its components are returned to the patient. It may also be located on the downstream end of the system, close to Y-junction 1037 in FIG. 10, and controlled by processor 1030 .

The disclosed embodiments may also include a tubing set for use in removing pathogenic T cells from a patient's blood. Such tube sets may be disposable and may include tube segments and other disposable components. Alternatively, the tubing set or parts thereof, such as the biological filter, may be reusable in the same patient. The tubing set may include one or more first stage regions including a blood separator, a leukocyte outlet, and a blood fraction outlet. The tubing set also contains a human leukocyte antigen (HLA)-peptide complex and has one or more primary inlets, one or more primary outlets, one or more recirculation inlets, and one or more recirculation outlets. A second stage area containing a biological filter may also be included. A recirculation loop within the tubeset may interconnect one or more recirculation outlets to recirculation inlets. One or more blood suction tubes may be configured to carry blood from the patient's body to one or more inlets of the first stage area. One or more intermediate tubes may be configured to carry blood from the leukocyte outlet of the first stage area to the primary inlet of the second stage area. One or more first stage bypass tubes may carry the blood fraction from the blood fraction outlet in the first stage area for return to the patient. And, at least one leukocyte return tube may be configured to carry leukocytes from the primary outlet of the second stage area for return to the patient.

FIG. 12A provides an example tubing set 1200 for use in removing pathogenic T cells from a patient's blood. For consistency, components such as those in FIG. 10 share the same reference numbers. Tubing set 1200 may include blood separation device 1004 and biological filter 1016 connected in the following manner. Inlet conduit 1028 connects the inlet of blood separation device 1004 . At the opposite distal end of inlet conduit 1028 may be some form of connector (not shown) for connecting the inlet conduit to a blood source. In one embodiment the connector may be a needle, in another embodiment it may be a luer connector or any other type of connector or cannula for drawing blood from a reservoir or patient. The blood separation device may have two or more outlets, one for white blood cells, and one or more outlets. A fractionated blood outlet conduit 1012 is connected to the blood fractionated outlet for returning the blood fraction to the patient. The region of the tubeset that contains the blood separation device 1004 may be considered the first stage region of the tubeset. Leukocyte conduit 1023 is connected to the inlet of biological blood filter 1016 and recirculation loop 1024 connects the outlet of biological filter 1016 to the inlet of the same filter. The treated leukocyte conduit 1035 is connected to the outlet of the biological blood filter for returning the treated leukocytes to the patient. The area of the tubeset that contains the biological filter 1016 may be considered the second stage area of the tubeset.

Conduits 1035 and 1012, like conduit 1028, have the same types of connectors/needles/cannulas as previously described for returning blood components directly to the patient or to reservoirs for indirect return to the patient. may contain one of Alternatively, as shown in Figure 12A, the conduits 1012, 1035 may be connected to a Y-junction 1037 that is connected to a connector on the outlet end of the Y-junction 1037, as previously described.

The tubing set conduits may be made of flexible plastic and sized such that the tubing fits within the race of a peristaltic pump used in a device for treating blood.

FIG. 12A is but one example and variations are possible within this disclosure. The primary inlet of the biological filter (ie, second stage area) and recirculation inlet may be common. For example, in FIG. 12B, a pair of inlet conduits and a pair of outlet conduits share a common filter inlet and outlet, respectively. It should be understood that each conduit may be connected at a unique inlet or may be connected to a junction serving a single inlet. Another exemplary variation of a biological filter connection is shown in Figures 12B-12D.

Only a single biological filter is shown in FIG. It is believed that more than one filter can be used to speed up the treatment process. In multiple filter embodiments, a single blood separation device may serve two or more filters. Alternatively, multiple blood separation devices may be used. In the case of multiple filters connected to a single blood separation device, multiple leukocyte conduits such as 1023 may supply multiple filters. In this embodiment, the associated therapeutic device may include a valve system that controls blood flow to each of the biological filters. The valve system may include a separate controllable valve on each leukocyte conduit, each valve controlled by processor 1030 .

Regardless of the embodiment, the length of each conduit is such that blood separation device 1004 and biological blood filter 1016 fit within interposed peristaltic pumps, such as pumps 1021, 1022, and 1031 in the figures. It may be sized to allow it to assume a pre-assigned position within each first stage area and second stage area on an associated device with sufficient conduit length.
A system to predictively adjust therapeutic regimens for patients with T cell-associated immune disorders

The present disclosure contemplates preventive measures in which potentially pathogenic T cells in the future can be predicted and prophylactically removed, for example, by using the biological filters described herein. To this end, the present disclosure provides systems for predictively adjusting therapeutic regimens for patients with T cell-associated immune disorders. Once potentially pathogenic T cells are identified, patients already receiving treatment for their disease can adjust their treatment regimen accordingly to halt future progression of the disease before it occurs. can do. Note that although the present disclosure provides examples of adjusting therapeutic regimens for T cell-related immune disorders, aspects of the disclosure in its broadest sense are not limited to T cell-related immune disorders. Rather, the aforementioned principles can also be applied to treat other diseases.

The term "system" according to this disclosure can include any device or group of devices that includes one or more processors capable of accessing and processing data. In the broadest sense, a system can be characterized by a processor. Alternatively, the system may have multiple components. For example, the system may be a suitably programmed computer, the computer including at least a processing unit and a memory unit. One or more computer programs can be loaded into the memory unit and executed by the processing unit. A loaded program can cause a computer to execute commands. The present disclosure further contemplates a machine-readable memory tangibly embodying a program of instructions executable by a machine to perform one or more methods of the present disclosure. For example, a computer program product embodied in a non-transitory computer-readable medium and executable by one or more processors, the computer program product containing instructions for causing one or more processors to execute commands. . The present disclosure also contemplates systems in which a suitably programmed computer may be connected to one or more input devices and/or one or more output devices. Exemplary systems include a computer interfaced to a flow cytometer or a system that counts, sorts, and detects cells such as T cells; Detect binding of T-cells and HLA-peptide complexes in patients with a protein chromatography system, such as a separate liquid chromatography system, and/or a fluorescence anisotropy, ITC, light scattering technique or a suitable absorption spectroscopy system and measuring systems. Exemplary output devices that can be connected to the system of the present disclosure transmit such notifications over one or more displays that can be useful in notifying medical professionals of possible disease progression to a network. an interface for outputting instructions to make a customized filter for a patient, or a 3D printer or other machine for making a biological filter.

The system may be configured to adjust the therapeutic regimen. A "treatment regimen" can include any course of treatment. For example, a biological filter may be selected or custom designed in conjunction with a therapeutic regimen to deplete a particular type of T cell from a patient. Adjustments to the therapeutic regimen can include changing one or more of the number of T cells targeted for depletion or the type of T cells targeted for depletion. Such adjustments can be made more predictively, as described below. As another example, a treatment regimen can be defined for a defined duration, dosage, route of administration (eg, oral, intravenous, etc.), and/or its effects in order to cure a disease and/or improve a patient's health. It may include one or more therapeutic agents or devices designed to manage or alleviate symptoms. For example, a therapeutic regimen may include orally administered pharmaceutical agents, which include a specific dosage of active ingredient in an oral composition (e.g., tablet, capsule, solution) at a specific frequency (e.g., 8 hourly, every 12 hours), for a specific period of time (e.g., 6 weeks, 12 weeks), and in a specific state (e.g., fed, fasted) when the patient is administered the drug. Become. The foregoing formulation examples are provided for illustration only, and they may or may not be mutually exclusive.

According to some disclosed embodiments, a system may include one or more processors. The term "one or more processors" is defined above and can include any physical device or group of devices having electrical circuitry that performs logical operations on one or more inputs. In some embodiments, one or more processors may include two or more processors. As noted above, each processor may have a similar structure, or the processors may be electrically connected or disconnected from each other, may be separate circuits, or may be in a single unit. It may have a different structure, which may be integrated into the circuit. When multiple processors are used, the processors may be configured to operate independently or in concert, may be co-located with each other, or may be co-located with each other; They may be combined magnetically, optically, acoustically, mechanically, or by other means that allow them to interact.

By way of example, FIG. 13 shows a system 1312 with one or more processors 1314. Although schematically illustrated as a single block, processor 1314 may comprise a single processor or multiple processors commonly located or spread across multiple locations within system 1312 . Processor 1314 may be connected to one or more servers 1316 via network 1318 . Alternatively or additionally, processor 1314 may be connected to processor-side data storage or memory (not shown) of network 1318 . In such situations, server 1316 may not be required as part of the system or may be augmented by local memory. Some or all of the processing functions may be performed remotely from one or more processors 1314 or remotely from system 1312 .

Consistent with disclosed embodiments, one or more processors receive first data related to treatment of a plurality of patients sharing common HLA and common peptides that cause activation of disease-associated T cells. may be configured to The first data may, for example, include information about specific patterns of how disease progresses in patients sharing common HLA and common peptides that cause activation of disease-associated T cells. Additionally or alternatively, the first data may include information regarding how patients sharing such commonalities responded to one or more therapeutic regimens. For example, the first data may reflect the possibility that previously inactivated T cells may have been activated in patients sharing commonalities during the course of therapy or disease progression. There is The first data may include information regarding therapeutics effective in removing T cells likely to be activated. Additionally, the first data may include probabilities and/or information that may ascertain the probability of a particular disease progression in a particular patient. The first data may also include other patient-related information about multiple patients, such as genetic information, information about current or past diseases or conditions, or other health- or biologically-related information. "Treatment-related primary data" are information related to the effect of the current treatment regimen on the medical condition, such as changes in symptoms experienced by the patient, changes in blood chemistry, or other biological effects. may include

As an example, the first data may be received as reflected in block 1412 of FIG. The first data may be stored on one or more servers 1416 and/or stored in a data structure, as shown in FIG. A data structure consistent with this disclosure may include any collection of data values and relationships between them. Data can be linear, horizontal, hierarchical, relational, non-relational, unidimensional, multidimensional, operational, unordered, object-oriented, centralized, distributed , in a custom fashion, or in any fashion that allows data access. As non-limiting examples, data structures may include arrays, associative arrays, linked lists, binary trees, balanced trees, heaps, stacks, queues, sets, hash tables, records, tagged unions, ER models, and graphs. . For example, data structures can be XML databases, RDBMS databases, SQL databases, or NoSQL alternatives for data storage/retrieval, such as MongoDB, Redis, Couchbase, Datastax Enterprise Graph, Elastic Search, Splunk, Solr, Cassandra, Amazon DynamoDB , Scylla, HBase, and Neo4J. A data structure may be a component of the disclosed system or a remote computing component (eg, a cloud-based data structure). The data in the data structures may be stored in contiguous or non-contiguous memory. Moreover, the data structures used herein do not require coexistence of information. It may be distributed, for example, over multiple servers which may be owned or operated by the same or different entities. Thus, the term "data structure" as used herein in the singular includes plural data structures.

Storing the first data on one or more network-accessible servers, such as server 1416, can transfer the first item of first data over the Internet, for example, where network 1418 includes the Internet. May allow to aggregate from sources. The predictive accuracy of the system is likely to increase as the amount of primary data from different patients increases. Alternatively, the first data may be stored locally in a memory device specifically associated with processor 1414 . Regardless of where the first data is stored, it may be received by processor 1414, and processor 1414 may perform functions described in more detail herein.

"Multiple patients sharing common HLA and common peptides that cause disease-associated T cell activation" refers to patient populations from which data can be predicted (e.g., less than about 10, about 20, about 50 , about 100, about 500, about 1,000, about 5,000, about 10,000, about 25,000, about 50,000, about 75,000, about 100,000, etc., or any integer number between 10 and 100,000 or more ) and usually suffer from the same T cell-related immune disease or category thereof, in which specific T cells (and their specific T cell receptors) A series of biochemical cascades occur upon encounter with the corresponding peptide presented by the cytoplasmic cytoplasmic cytoplasmic cytoplasm (Peptide), which activates T cells to protect against specific targets (peptides), including aberrant immune responses such as autoimmune responses or An immune attack can be carried out.

Consistent with disclosed embodiments, the data may include progression of common peptides that activate T cells over time, with further progression of the disease more different peptides activate disease-associated T cells early. activate more than For example, in the early stages of disease progression, a smaller group of peptides may activate disease-triggering T cells. However, the list of peptides that activate T cells that cause this disease can change and grow over time. Such progression is not unique to a particular patient and may be demonstrated across a group of patients with disease-inducing peptide progression common to that group. The data received may include such information. Thus, the system according to the present disclosure allows therapeutic regimens that may not effectively treat disease in patients because the disease changes as it progresses and pathogenic T cells may later be activated by different or additional peptides. can aim to improve. In such situations, the treatment-relevant data may include information about peptides that are common to multiple patients and that activate disease-associated pathogenic T cells in patients at one or more different stages of disease. Multiple patients who share common HLA and common peptides that activate disease-associated T cells not only share the same disease, but also share the same or similar peptides that activate disease-causing T cells. It can be a shared individual.

In some embodiments, one or more processors that can be configured to receive second data associated with a particular patient having common HLA and common peptides, wherein the first set of peptides is a disease One or more processors can be configured that are at a disease stage that activates a first subpopulation of relevant T cells and a second set of peptides does not activate a second subpopulation of disease-related T cells. Receiving the second data may include accessing data regarding the particular patient. Certain patients may be targets of treatment, and medical professionals may, in the future, target disease progression where certain peptides may activate T cells that currently do not activate T cells as a result of disease progression. would be interested in determining whether The second data may include, for example, information characterizing peptides that are currently causing disease in a particular patient. Alternatively, if a particular patient has not yet exhibited symptoms of disease, the second data may include information regarding peptides expected to activate the particular patient's T cells. Alternatively, or additionally, the second data may include information about a particular patient's HLA type, or any other biological or health information that may be correlated with disease.

As an example, second data may be received, the second data relating to a particular patient's T cell activation profile, as shown in block 1414 of FIG. In the exemplary embodiment of FIG. 13, the second data may be received by processor 1314 . Such reception may occur when a medical professional enters data into memory for access by processor 1314, or as a result of data imported over a network. The second data may include information received from analytical medical equipment used to characterize the patient's medical condition. This can occur, for example, via a data connection between processor 1314 and a medical device (not shown). In some embodiments, the second data may include various types of data received by processor 1314 . These data may include information about patient peptides, HLA, and other biological or health information about a particular patient.

In certain embodiments, the second data can be determined by analyzing information associated with HLA typing and related peptides. Methods and techniques that can be utilized to identify HLA types and related peptides, and subsequent data analysis, include, but are not limited to, the procedures described in Example 8 of this disclosure. For example, HLA typing can be based on either oral swab DNA testing or blood analysis, where information about peptides can be based on analysis of tissue-specific and disease-related biological fluids. In another example, analysis of related peptides can include stripping peptides from HLA complexes and determining peptide sequences. Removal of peptides bound to a patient's HLA can be achieved by protein chemistry techniques such as changing the pH value of biological fluids to disrupt interactions between peptides and HLA, denaturation of peptides using agents such as DMSO can be achieved in several different ways, including In some embodiments, analyzing data associated with related peptides can include analyzing cerebrospinal fluid peptide data if the particular patient has multiple sclerosis. If a patient has a T cell-associated immune disease, such as multiple sclerosis, the systems and methods provided herein can predictively adjust the therapeutic regimen to deplete the T cells. In the case of multiple sclerosis, regimen adjustments may be made in conjunction with myelin-derived peptides or non-myelin central nervous system proteins, including aquaporin channels. Myelin may contain a mixture of proteins rather than a single protein, and immunogenic peptides include myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), myelin proteolipid protein (PLP), opaline Proteins, oligodendrocyte-specific protein (OSP), myelin-associated glycoprotein (MAG), or combinations thereof. Non-limiting examples of myelin peptides include the exemplary peptides described above.

After biosynthesis, proteins often undergo post-translational modifications. Similarly, HLA-binding peptides in HLA-peptide complexes can be derived from proteins that have undergone post-translational modifications, such as phosphorylation and glycosylation, or can be derived from one or more mutations (e.g., amino acid substitutions). , deletions, insertions) or may be truncated. Accordingly, disclosed embodiments of the present disclosure include embodiments of systems in which the first set of peptides and the second set of peptides can be variants of the same peptide. A "variant of the same peptide" may include copies of the same peptide that may be subject to modifications and mutations as described above. Alternatively, the first peptide set and the second peptide set can be different from each other. In addition to depleting a patient's second subpopulation of disease-associated T cells that are inactive against the second peptide set, the disclosed embodiments provide disease-associated T cells that are active against the first peptide set. It may further comprise depletion of the patient's first subpopulation of T cells. The present disclosure is not limited by the method by which the first and second subpopulations of disease-associated T cells are depleted. For example, remedial action may be taken to simultaneously deplete a first subpopulation of disease-associated T cells and a second subpopulation of disease-associated T cells. Alternatively, to sequentially remove a first subpopulation of disease-related T cells and a second subpopulation of disease-related T cells, for example, the second subpopulation of disease-related T cells and then the first subpopulation of disease-related T cells. Remedial action may be taken to eliminate subpopulations of , or vice versa.

Disclosed embodiments may include using the first data set to identify that a second set of peptides in a particular patient corresponds to further progression of the disease. For example, data obtained from one or more patients reflected in a first data set indicates that other peptides (second set) that are not currently disease-causing in a particular patient will be disease-causing in the future. May indicate possible disease progression. In the simplest way, this can be determined by identifying a single patient who exhibits progression. For a more reliable prediction, it would be beneficial to determine that the group of individuals informed by the first data show progression.

In alternative embodiments, additional information may be used to help determine that a second set of peptides in a particular patient corresponds to further progression of the disease. Although not required, additional information may include data on other factors that correlate with disease progression. For example, the first data set may contain a large amount of information about the population and biological and health information related to individuals within the population. A machine learning algorithm running on the first data may identify a relationship between one or more biological or health information and a particular disease progression. In this way, prediction accuracy can be increased through artificial intelligence.

A machine learning algorithm or model can be trained using training examples. Some non-limiting examples of such machine learning algorithms are classification algorithms, data regression algorithms, segmentation algorithms, support vector machines, random forests, adjacency algorithms, deep learning algorithms, artificial neural network algorithms, convolutional neural network algorithms. , recurrent neural network algorithms, linear machine learning models, non-linear machine learning models, ensemble algorithms, and the like. For example, trained machine learning algorithms include prediction models, classification models, regression models, clustering models, segmentation models, artificial neural networks (deep neural networks, convolutional neural networks, recurrent neural networks, etc.), random forests, support vector machines, etc. can include an inference model of In some examples, a training example may include exemplary inputs and desired outputs corresponding to the exemplary inputs. Further, in some embodiments, a trained machine learning algorithm that uses training examples can produce a trained machine learning algorithm that estimates outputs for inputs not included in the training examples. can be used to In some embodiments, engineers, scientists, processes and machines that train machine learning algorithms may further use validation and/or test examples. For example, validation and/or test examples include inputs with desired outputs corresponding to exemplary inputs, and are validated using trained and/or intermediately trained machine learning algorithms. Estimate outputs for exemplary inputs of examples and/or test examples, compare estimated outputs to corresponding desired outputs, and use trained and/or intermediately trained machine learning algorithms. , can be evaluated based on the results of the comparison. In some examples, a machine learning algorithm can have parameters and hyperparameters, where the hyperparameters are manually set by a person or by a process external to the machine learning algorithm (e.g., a hyperparameter search algorithm). Automatically set, the parameters of the machine learning algorithm are set according to the machine learning algorithm according to the training examples. In some implementations, the hyperparameters are set according to the training examples and validation examples, and the parameters are set according to the training examples and the selected hyperparameters.

In some embodiments, a trained machine learning algorithm (also called a trained machine learning model) can be used to analyze the input and generate the output. In some examples, a trained machine learning algorithm can be used as an inference model that produces an estimated output when given an input. For example, the trained machine learning algorithm may include a classification algorithm, the input may include samples, and the estimated output may include sample classifications (guessed labels, guessed tags, etc.). good. In another example, a trained machine learning algorithm may include a regression model, the input may include samples, and the estimated output may include estimates for the samples. In yet another example, the trained machine learning algorithm may include a clustering model, the input may include samples, and the estimated output includes an assignment of the samples to one or more clusters. obtain. In a further example, the trained machine learning algorithm may include a classification algorithm, the input may include the image, and the inferred output may include the classification of the items shown in the image. In some embodiments, a trained machine learning algorithm includes one or more formulas and/or one or more functions and/or one or more rules and/or one or more procedures, and the input is used as input to formulas and/or functions and/or rules and/or procedures and the inferred output is the output of formulas and/or functions and/or rules and/or procedures (e.g. formulas and/or functions and/or /or selecting one of the outputs of the rules and/or procedures, using formulas and/or functions and/or statistical measures of the outputs of the rules and/or procedures, etc.).

In some embodiments, artificial neural networks can be configured to analyze inputs and generate corresponding outputs. Some non-limiting examples of such artificial neural networks include shallow artificial neural networks, deep artificial neural networks, feedback artificial neural networks, feedforward artificial neural networks, autoencoder artificial neural networks, stochastic artificial neural networks. , time-delay artificial neural networks, convolutional artificial neural networks, iterative artificial neural networks, long-term memory artificial neural networks, etc. In some embodiments, artificial neural networks may be manually configured. For example, the structure of the artificial neural network can be manually selected, the type of artificial neurons of the artificial neural network can be manually selected, the parameters of the artificial neural network (such as the parameters of the artificial neurons of the artificial neural network) Can be manually selected. In some examples, machine learning algorithms may be used to construct artificial neural networks. For example, a user can select hyperparameters for an artificial neural network and/or a machine learning algorithm, which uses the hyperparameters and training examples to generate, for example, gradient descent, stochastic gradient Descent, mini-batch gradient descent, and backpropagation can be used to determine the parameters of artificial neural networks. In some embodiments, an artificial neural network can be created from two or more other artificial neural networks by combining the two or more other artificial neural networks into a single artificial neural network. In the broadest sense, using the first data to determine that the second set of peptides in a particular patient corresponds to further disease progression does not require machine learning or artificial intelligence.

As implemented as an example, using the first data to determine that a second set of peptides in a particular patient corresponds to further progression of the disease can occur at block 1416 of FIG. This functionality may be accomplished using processor 1314 in FIG. 13, as an example. In that case, the first data set may be located on the server 1316 and the processor 1314 may retrieve relevant data and arrive at a decision. Alternatively, processor 1314 may be used to transmit information regarding a particular patient over network 1318 to server 1316 or to one or more processors (not shown) associated with server 1316 . In this manner, decisions that may include additional relevant information may be made remote from processor 1314 and returned to processor 1314 .

Regardless of where the decision-making processor is located, a second set of peptides that have not yet activated disease-associated T cells that are later predicted to do so is indeed associated with late stages of disease. can be configured to check This determination can be made, for example, by comparing peptides that do not yet activate disease-associated T cells to known biomarkers for more advanced stages of the disease. For example, multiple sclerosis can be divided into three main patterns, as described herein.

In some embodiments, determining that the second set of peptides corresponds to late progression of the disease involves comparing disease-related parameters including years from onset, Neurological Symptom Scale (EDSS) and treatment, HLA typing analysis; and analysis of peptides presented by the corresponding HLA proteins. These disease-related parameters may be useful factors for predicting disease progression, especially if such factors correlate with disease patterns. Correlations can be identified by machine learning, as described above.

If a peptide is identified in one or more patients that has not yet activated disease-associated T cells, action can be taken to prevent further progression of the disease in that particular patient. In system embodiments, this may be performed with the aid of one or more processors. For example, the one or more processors improve for removing a second subpopulation of disease-associated T cells from the patient before the second set of peptides activates the second subpopulation of disease-associated T cells. It may be configured to take action. Taking "corrective action" may include developing preventive strategies. For example, a biological filter according to the present disclosure can be used to prevent pathogenic T cells from being removed from the patient's circulation even before these cells are activated toward specific targets in the body. Can be used as therapy. In this case, taking remedial action may involve determining the characteristics of such a filter for a particular patient. Additionally or alternatively, taking remedial action may include outputting such characteristic information to a display, transmitting such characteristic information over a network to a medical professional or organization, one or more of: transmitting the characteristic information to a filter manufacturer to enable filter construction for biological filters, or outputting the characteristic information to a memory associated with the machine or system that makes up the biological filter can contain.

As an example, the remedial action is shown in block 1418 of FIG. 14 and may be implemented by processor 1314 (or another processor accessed over a network such as the Internet). In a sense, remedial action may include displaying information regarding disease progression on a display, such as display 1320 .

Remedial action may include adjusting the patient's treatment based on the identified second set of peptides. In one embodiment, the adjustment may include notifying the medical institution of the need to change treatment protocols so that appropriate action can be taken by the medical institution. In another embodiment, adjusting includes developing instructions that enable the machine to create a biological filter that reflects a change in patient treatment from a filter previously used with the patient. obtain.

Thus, in a sense, remedial action may simply involve issuing instructions to eliminate the second subpopulation of disease-associated T cells. Such instructions may be generated using a computer program readable by a computer to execute the commands. The instructions may be provided in a form requiring further translation, or may include the output of data for use in constructing filters containing the second set of peptides.

Consistent with some disclosed embodiments, the one or more processors are further configured to identify additional sets of consensus peptides that do not activate disease-associated T-cells and that additional peptide sets are associated with further progression of the disease. and remedial action may be taken to eliminate disease-related subpopulations from the patient before additional peptide sets activate additional subpopulations of disease-related T cells. For example, disease progression may change more than once over time. That is, as the disease progresses, additional sets of peptides other than the first and second set induce or can be expected to induce T cell activation. In such cases, embodiments of the present invention can identify these additional peptide sets and take remedial action to remove them before they have a chance to activate T cells. Remedial actions taken with additional peptides may be similar to those taken with the second set of peptides. Accordingly, in some embodiments, treatment may be adjusted based on the additional peptide sets identified. This can occur by issuing instructions to remove additional subpopulations of disease-associated T cells, as described above. Such instructions may be generated on one or more output devices or systems, such as those described above, using a computer program readable to execute commands by a computer. In further examples, the one or more processors can be further configured to take remedial action including outputting data for use in constructing filters that include additional peptide sets. Additional consensus peptide sets that do not activate disease-associated T cells, but may activate with disease progression, may be removed along with or after the first and/or second peptide set. In one embodiment, remedial measures are taken to simultaneously eliminate the first, second and additional subpopulations of disease-associated T cells.

Although the above-described embodiments have been described in relation to a system for predictively adjusting therapy, it should be understood that references to the system are for exemplary purposes only. The same principles may be implemented in any method or computer readable medium within the scope of this disclosure. For example, the process illustrated in Figure 14 may occur without a processor or system, or using a different system. Similarly, the process illustrated in FIG. 14 and related description herein may be implemented in a computer-readable medium containing instructions for causing one or more processors to perform such methods.
Methods of removing T cells from a patient

The disclosed embodiments may include methods of removing cells from a patient or, more generally, methods of removing cells from biological fluids. The fluid can be any of about 40 or more biological fluids. As used herein, the term "biological fluid" refers to a bodily fluid or fluid derived from the body of a mammal, such as a human. Non-limiting examples of biological fluids include whole blood, serum, plasma, cerebrospinal fluid, synovial fluid, alveolar lavage, pancreatic juice, gastrointestinal lavage, peritoneal lavage, lymph, bone marrow, amniotic fluid, semen, pleural effusion, breast milk, heart. Includes membrane fluid, saliva, feces, bile, and urine.

The depleted cells can be T cells, non-T cells, pathogenic cells, or non-pathogenic cells, depending on the intended purpose of depletion. One non-limiting example of the purpose of cell ablation may include removing specific cells known or suspected of causing disease. Elimination of the triggering cells may alleviate the disease.

Such methods may involve obtaining a biological fluid containing target cells from a patient. A biological fluid containing specific cells can then be extracorporeally flowed through a media host material that selectively binds only specific cells. In this way, certain cells can be trapped in the medium and the remaining untrapped biological fluid can be returned to the patient. Also, target cells in the patient's blood or other biological fluid can be removed in this manner.

For illustrative purposes, reagents and instruments are described below with respect to several examples. It should be understood that the examples, reagents and equipment are exemplary only.

The disclosed methods can be used with patients. The term "patient" can include humans or other mammals. In some embodiments, methods of depleting specific T cells are contemplated. The term "specific T cells" has also been previously described.

In some embodiments, T cells that do not express the particular T cell antigen receptor or targeted receptor cannot be removed. The term "T cells" mentioned above may include any type of lymphocyte that develops in the thymus and plays a central role in the immune response. In some embodiments, the specific T cells are one or more of helper CD4+ T cells, cytotoxic CD8+ T cells, memory T cells, regulatory CD4+ T cells, natural killer T cells, mucosa-associated invariant T cells. and/or γδT cells. Alternatively, or in addition, specific T cells may comprise at least one of CD4+ cells or CD8+ cells.

Target T cells may be pathogenic or non-pathogenic. Pathogenic T cells may play a similar role as nonpathogenic T cells, but pathogenic T cells can recognize self-structures and substances and attack them. As used herein, the term "pathogenic cell" refers to any cell, either endogenous or exogenous, that may be associated with disease or other affliction. By targeting and eliminating pathogenic cells, the patient's disease may be alleviated. Nonpathogenic T cells are targeted for elimination, for example, if a particular lineage is expected to evolve to the point that current nonpathogenic T cells may become pathogenic in the future. good too. Thus, active elimination of non-pathogenic cells may prevent later manifestations of disease.

Pathogenic cells can be associated with any one of the autoimmune diseases described herein. In certain embodiments, the pathogenic cell is multiple sclerosis, lupus, celiac disease, Sjögren's syndrome, polymyalgia rheumatoid arthritis, ankylosing spondylitis, type 1 diabetes, alopecia areata, vasculitis, autoimmune hepatitis , autoimmune lymphoproliferative syndrome (ALPS), autoinflammatory disease, Goodpasture syndrome, Lambert-Eaton syndrome, antiphospholipid syndrome (APS), neuromyelitis optica (NMO), paraneoplastic syndrome, primary cholangitis, stiff It may be associated with autoimmune diseases including, but not limited to, Parson's syndrome (SPS), antiphospholipid antibody syndrome (APS), or temporal arteritis.

In other embodiments, pathogenic cells may be associated with cancer diseases, such as hematologic cancers. Hematological cancers include leukemia, non-Hodgkin's lymphoma, Hodgkin's lymphoma, multiple myeloma, and other blood cell cancers. In other embodiments, the cancer disease may be solid. Solid cancers include lung cancer, breast cancer, colorectal cancer, pancreatic cancer, liver cancer, prostate cancer, or other solid tumors that form in tissues.

A method of removing specific T-cells, pathogenic cells, or non-pathogenic cells can comprise obtaining a biological fluid from a patient. Where the biological fluid comprises blood, references herein to blood may include either whole blood or blood fractions. As used herein, the term "blood" refers to the body fluid present in humans and other organisms that transports substances, including nutrients and oxygen, to cells and transports metabolic waste products away from cells. Point. As used herein, the term "blood fraction" refers to subcomponents of whole blood. A blood fraction may include one or more of plasma, white blood cells, red blood cells, and platelets. Biological fluids can also include cerebrospinal fluid (CSF). As used herein, "cerebrospinal fluid (CSF)" refers to the clear, colorless fluid found in the brain and spinal cord. In some embodiments, the biological fluid can include bone marrow. As used herein, the term "bone marrow" refers to semi-solid tissue found in the spongy or cancellous portion of bone and capable of producing white blood cells, red blood cells and platelets. In other embodiments, the biological fluid may comprise synovial fluid. As used herein, the term "synovial fluid" refers to the non-Newtonian fluid found within the synovial joint cavity and capable of providing lubricity to the joint surfaces. In other embodiments, the biological fluid may comprise fluid obtained from alveolar lavage. As used herein, "alveolar lavage fluid" refers to fluid that is introduced into the lungs and subsequently withdrawn. In some embodiments, the biological fluid can include ascites. As used herein, the term "ascites" refers to fluid within the abdominal cavity that can lubricate the tissues lining the abdominal wall and pelvic cavity. Thus, as used herein, the term "drawing" in relation to biological fluids refers to any mechanism for removing biological fluids from a patient.

This concept is conveyed by way of example at block 1502 of FIG. 15, where the biological fluid is generally indicated as being taken from a patient. Such processes of obtaining biological fluids from a patient may include, for example, aspiration and/or drainage. Aspiration includes the removal of liquid from microorganisms by aspiration and can be performed, for example, via a needle or catheter. If the biological fluid is blood, the blood can be removed by inserting a needle into a vein, which is connected to a collection container or tubing set.

The disclosed embodiments may further include extracorporeal flow of a biological fluid through a media host material that selectively binds only specific cells, thereby trapping specific cells in the media. The terms "vehicle" and "selective binding" have been previously described. At block 1504 of FIG. 15, the specific cells (or in other embodiments, other target substances) are extracted to capture the target substances (eg, the specific cells) when the biological fluid is extracorporeally flowed through the host medium. , can be preferentially attached in any manner. In a broad sense, binding includes any process of combination, adhesion, coupling, or reaction that causes target cell removal.

Many types of surface media can be used including solids, semi-solids or fluids. When solid or semi-solid, the medium can have any form. Examples provided above in FIGS. 2A-2D include sheet materials, fibers, beads, and sponge-like materials. Other examples include mesh structures, liquids and gels. But these are only examples. This method can be practiced regardless of the particular host material.

Likewise, the composition of the media may vary depending on the intended use. By way of example only, media can include inert, non-synthetic, synthetic, polymeric, high performance thermoplastics, polysulfone, polysulfone derivatives, glass matrix, silicon matrix, polydimethylsiloxane (PDMS), polycarbonate, polyetherimide (Ultem), tritane. , polyelectrolyte, polyacrylic acid, or poly(2-aminoethyl)acrylamide in one or more ways. Alternatively or additionally, the medium may be polyacrylic acid present at about 5-40 weight percent; polysulfone present at about 60-95 weight percent; polystyrene, polyethylene glycol (PEG) or PEG derivatives, capable of intermolecular cross-linking PEG density is maximized by creating a six-armed star molecule of PEG, and/or avidin, streptavidin, or any form thereof. Again, these are merely examples and should not be considered limiting of the present disclosure in its broadest sense.

FIG. 16 is a schematic diagram illustrating an exemplary embodiment of media having an inert surface 1604. FIG. As an example, the inert surface may contain streptavidin. Media 1604 is shown as a sheet, but may be in any form including, but not limited to, the forms shown in Figures 2A-2D.

As shown in FIG. 16, medium 1604 may host binding material 1608 that selectively binds and captures biological material such as cells 1606 . For example, cell 1606 may be a pathogenic T cell and may adhere to the medium in any manner, including through covalent bonds, non-covalent interactions or adsorption. Non-covalent interactions include hydrogen bonding, ionic interactions, hydrophobic interactions, or pi stacking. In certain embodiments, binding material 1608 may comprise a protein, in which case reference number 1608 may indicate the protein. In some embodiments, binding material 1608 comprises an antibody, in which case reference number 1608 may represent the antibody. For example, antibodies can recognize specific epitopes on a biological material (eg, cells 1606), thereby capturing the biological material and immobilizing it on the medium. The term "antibody" as used herein may include Fab, Fab', F(ab')2, Fabc, Fv fragments, or any other antigen-binding fragment or antigen-binding antibody portion thereof. . In certain embodiments, antibodies may comprise monoclonal antibodies, polyclonal antibodies, recombinant antibodies, chimeric antibodies, humanized antibodies, human antibodies, or antigen-binding fragments or portions thereof. The medium may contain multiple different antibodies that recognize multiple different antigens on multiple different biological substances.

Although binding material 1608 may selectively bind only to specific cells, binding material 1608 may initially bind host medium 1604 . Thus, the use of the phrase "selectively binds only to specific cells" refers to the selective binding of cells (or other biological substances) trapping processes, which may occur through binding. It is not the mechanism that connects medium 1604 to bonding material 1608 .

In some embodiments, the selectively binding host material comprises a human leukocyte antigen (HLA). HLA can bind to peptides to form HLA-peptide complexes. In one example, HLA-peptide complexes can recognize specific epitopes on biological material (eg, T cells). By way of example, if the medium may contain avidin, streptavidin or any variant thereof, the capture material may be linked to biotin that can interact with avidin, streptavidin or variants thereof on the surface of the medium. , thereby fixing the capture material to the medium. In another example, the medium may contain free carbonyl groups, amine groups, maleimide groups, or any other functional groups that can interact with functional groups on the capture material, thereby immobilizing the capture material to the medium. . In yet another embodiment, the medium comprises a blend of polysulfone and polyacrylic acid, and the capture material is a protein that binds to the medium via the carboxyl groups of the polyacrylic acid. Additionally, mixtures of polysulfone and polyacrylic acid can be modified to contain amine groups, and proteins can bind to media via reaction with the amine groups. In a further example, a blend of polysulfone and polyacrylic acid can be modified to include maleic acid, maleimide groups, or analogs thereof. Maleic acid, maleimide groups or analogues thereof can be extended with a carbohydrate linker. The capture material may bind to the medium through reaction with maleic acid, maleimide groups or analogues thereof.

As a schematic illustration, medium 1702 containing medium 1706 containing HLA-peptide complex 1704 and antibody 1708 is shown in FIGS. 17A-17B. Media 1702 and 1706 are shown in sheet form, but may be in any form including, but not limited to, the forms shown in FIGS. 2A-2D.

In some embodiments, the capture material may comprise HLA proteins and may further comprise peptides to form HLA-peptide complexes. HLA-peptide complexes can be placed on the medium via, for example, maleic acid, maleimide or analogues thereof.

In some embodiments, HLA-peptide complexes can be recombinantly designed and expressed. For example, HLA proteins may be designed to include fusion proteins or tags. In another example, HLA proteins can be designed to include a cysteine residue at the C-terminus. In some embodiments, HLA proteins may be linked to the C-terminal cysteine via a peptide linker. Alternatively, HLA-peptide complexes can be obtained endogenously from an individual, such as a patient. In some embodiments, HLA proteins include HLA I and/or HLA II. In some embodiments, the HLA proteins of the HLA-peptide complex can be cleaved. In certain embodiments, truncation results in a C-terminal cysteine. The HLA-peptide complexes can react with maleimide or its analogues on the medium, thereby immobilizing the HLA-peptide complexes on the medium. In certain embodiments, a recombinantly-designed and expressed HLA complex may comprise a recombinant protein similar to an individual's protein. In preferred embodiments, the recombinantly-designed expressed or endogenous HLA complex may comprise type I or type II HLA proteins. In some embodiments, recombinantly designed HLA proteins may contain peptide binding grooves for binding to endogenous or synthetic peptides that may be subsequently presented. In certain embodiments, the loaded endogenous or synthetic peptide can be a disease-associated immunogenic peptide. In some embodiments, the specific T cell is a T cell specific for an antigenic peptide derived from a protein associated with an autoimmune disease, including any one of the exemplary autoimmune diseases described herein. Contains receptors. In certain embodiments, autoimmune diseases may include multiple sclerosis, type 1 diabetes, myasthenia gravis, or Crohn's disease. In some embodiments, HLA-peptide complexes can recognize specific T cell receptors on T cell populations and thereby trap T cells. In some embodiments, T cells may comprise CD4+ and/or CD8+ T cells. In some embodiments, the HLA-peptide complex may comprise multiple different HLA-peptide complexes, each of which may recognize different T cell receptors on multiple T cell populations.

Extracorporeally flowing the biological fluid through the medium may include flowing the biological fluid through the medium once or continuously recirculating the biological fluid multiple times or over a period of time. Multiple passes are required because the total volume of biofluid may not contact enough of the filter surface to bind a sufficient percentage of the cells to be removed in any one pass. obtain. Of course, the amount of recirculation, if any, can be said to be a function of the particular filter design and the particular use case.

The disclosed embodiments may also include returning the biological fluid free of entrapped cells to the patient. The step of returning the cells to the body can occur after sufficient time has elapsed to ensure that the desired amount of target cells has been removed by the filter. At block 1506 of FIG. 15, the cells can be returned in any manner. For example, they may be returned via a tubing set extending from the outlet of the filter to the patient, or, for example, the cells may be harvested and returned at a later time. To facilitate the efficiency of the filter, for example in the case of blood, the blood may first undergo an initial separation to separate the portion of the blood that contains T cells from the portion that does not. The T cell portion can then be circulated through the biological filter and the remaining portion either immediately returned to the patient or retained for later return.

These processes can be facilitated by using one or more peristaltic pumps and one or more reservoirs. In certain embodiments, the biological fluid can be enriched before returning to the patient. As an example, nutrients or pharmaceutical compositions may be added prior to return.
Method for making a personalized biological filter for selectively removing pathogenic cells from a patient

Some disclosed embodiments relate to methods of making personalized biological filters for removing pathogenic cells from a patient. Such biological filters, according to embodiments disclosed herein, may be useful in treating disease in patients caused by pathogenic cells such as T cells. Alternatively, biological filters containing HLA-peptide complexes containing specific immunogenic peptides attack pathogenic cells that attack self-proteins in the body, causing activation of those cells and destruction of self-proteins and cells. can be removed using Since diseases that induce HLA-peptide complexes can vary from patient to patient, filters can be individualized to a particular patient's biology. For example, analysis may be performed on a patient to identify one or more HLA types of the patient and to identify the identity of one or more pathogenic peptides. Filters may then be constructed with HLA-peptide complexes specific to the patient's disease, thereby individualizing the filter to the patient. Alternatively, various filters may be stocked with a common combination of HLA-peptide complexes and the appropriate filter selected after patient analysis is performed. Such filters, which are specifically selected from storage for patient-specific HLA-peptide complex combinations and installed, are considered personalized filters within the meaning of this disclosure. As discussed below, biological filters consistent with this disclosure can include HLA-peptide complexes bound to inert filter surface media. This and other examples are discussed in more detail below.

The filter may have any suitable form capable of removal function. For example, it may be in the form of or configured to include one or more sheets of material to which biofluid components bind, adhere, or react, or even other structures that provide a similar effect. good. Such structures may include, for example, meshes, fibers, gels, beads, scaffolds, or any other material having a surface area configured for biological filtration.

A biological filter consistent with embodiments of the present disclosure may be configured to trap cells, proteins, nucleic acids, lipids, polysaccharides, or any other biological material. For example, filters may contain proteins or be immobilized with proteins that recognize and trap pathogenic or non-pathogenic cells, depending on the function the filter is designed to accomplish. In some embodiments, pathogenic cells may have the same role as non-pathogenic cells, except that they recognize and attack self-structures and substances. As an example, a filter may be designed to remove one or more of many pathogenic cells associated with many diseases. For example, filters may be designed to remove pathogenic lymphocytes.

Consistent with some disclosed embodiments, a method of making a personalized biological filter can include identifying a patient's HLA type. HLA typing for a particular patient can be performed using any technique that identifies one or more HLA types of the patient, as described above. Accordingly, identification of a patient's HLA type is generally not limited to the method by which the HLA type is obtained or the biological fluid from which it is obtained, as reflected in block 1812 of FIG. 18 by way of example. Examples of such fluids include, without limitation, blood, cerebrospinal fluid, or any other suitable bodily fluid from which HLA typing can be determined, including those previously described herein. All examples of biofluids that have been collected are included.

In some embodiments, the method of creating a personalized biological filter comprises identifying one or more immunogenic peptides associated with a patient's disease or immunogenicity associated with a patient's disease. This may involve identifying one or more clones of cells that are recognized and activated by the peptide. The term "peptide" generally refers to a short chain of amino acids linked together by peptide bonds. Immunogenicity of peptides may be measured by standard means. In one exemplary process for identifying one or more immunogenic peptides, a fluid sample taken from a patient can be processed to separate cells from the fluid. Cells may then be lysed and the protein fraction collected. This results in a mixture of all proteins expressed by the cell and many HLA-peptide complexes can assemble. Immunoprecipitation can then be performed on the protein fraction by introducing antibodies into the protein mixture known to bind HLA complexes. In this way, HLA complexes can be separated from other proteins. Peptide stripping can then be performed on the HLA-peptide complex to dissociate proteins from HLA. Mass spectrometry may then be performed on each dissociated peptide to identify those peptides associated with a particular disease. More specifically, mass spectrometry reveals the determinant sequence for each peptide. These sequences can then be compared to sequences known to be associated with disease-linked proteins. For example, a sequence can be entered into a search engine to determine whether related peptides are associated with disease. For example, in the case of multiple sclerosis, myelin-associated proteins would be identified. In its broadest sense, embodiments of the present disclosure are not limited to particular mechanisms for identifying particular disease-associated peptides. Thus, block 1814 of Figure 18 generally refers to identifying one or more immunogenic peptides associated with a disease, without specifying a particular method of practice.

A group of more specific HLA-peptide complexes can be identified by using bioinformatics databases to identify peptides with the strongest binding affinity to the patient's HLA. Once these front-runners are identified, a test surface or groups of test surfaces can be constructed and anchored at discrete regions to which synthesized HLA-peptide complexes can bind. A fraction of the patient's blood called peripheral blood mononuclear cells (PBMC) is then stained on the test surface area. This process reveals which HLA-peptide complexes bind to T cells and the circulating concentration of T cells from a given clone can be determined. For example, by labeling PBMCs and using a process such as fluoroscopy, the volume of T cells that bind to each test area may be measured. HLA-peptide complexes associated with the highest binding signaling regions may reflect the amount of peripheral T cells removed. Significant binding indicates HLA-peptide complexes to be included in the personalized treatment filter for the patient.

In certain embodiments, multiple disease-associated immunogenic peptides may be identified or analyzed. For example, a series of HLA-peptide complexes may be identified as causing disease. If so, many such complexes can be tested to determine to what extent they induce disease. In some embodiments, identified peptides can be quantified. If so, those meeting a threshold (eg capacity to bind T cells in the test) can be selected for use in the filter. Identification of peptides can be accomplished by amino acid sequencing. Additionally, such peptides can be compared to databases of disease-associated immunogenic peptides to obtain relevant information about the peptides. For example, as discussed in more detail herein, the binding affinity of peptides to particular HLAs expressed in patients can be determined through the use of commercially available or publicly available databases. In some embodiments, a peptide's binding affinity for a particular HLA can be quantified. By quantifying binding affinities, peptide-HLA combinations with the highest binding affinities can be selected, thereby guiding the design of biological filters.

Thus, in some embodiments, identifying or analyzing an immunogenic peptide may comprise comparing the peptide to a database of disease-associated immunogenic peptides that contain peptide binding affinities to HLA complexes. If a patient's HLA type is included in the analysis, such a comparison will help narrow the pool of disease-causing HLA-peptide complexes for that patient.

In certain embodiments, peptide identification or analysis can be determined via cerebrospinal fluid analysis or tissue-specific disease association analysis. As an example, tissue from an affected individual can be harvested. A population of HLA complexes with linked or loaded peptides can be isolated from the cells of the diseased individual. Peptides can then be separated from the HLA complex, eg, by chemical means. The isolated peptides can then be sequenced and analyzed for frequency in order to associate them with the individual's particular disease. Such identification of one or more immunogenic peptides associated with patient disease is generally reflected in block 1814 in FIG. 18, among other identification methods.

A method of making a personalized biological filter can involve recombinantly or endogenously produced HLA complexes corresponding to the patient's determined HLA type and one or more immunogenic peptides. HLA types may include HLA I or HLA II or both. The specific complexes generated may be based on analysis of binding affinities between HLA expressed by the patient and one or more identified immunogenic peptides. One or more combinations of HLA and immunogenic peptides can be selected for production/production. Endogenous production of HLA complexes can include obtaining endogenous HLA complexes from a patient. Recombinant production of HLA complexes involves incorporating the recombinant DNA of interest into a system capable of transcribing the DNA into mRNA and translating the mRNA into an amino acid sequence corresponding to the recombinant HLA complex. can be included. An example of a DNA plasmid is pET-21d (+) or any other available expression vector, which can be transfected into bacterial expression systems such as E. coli (e.g. BL21 or B834 strains) for protein production. . Other expression systems include, but are not limited to, insect cells, mammalian cells, cell-free expression systems, or any other suitable system. Recombinant HLA complexes can be altered from endogenous HLA complexes. The generation/generation of HLA complexes corresponding to the patient's HLA type is reflected in block 1816 of FIG. 18 as an example.

In some embodiments, an HLA complex can comprise an HLA protein and an antigenic peptide that is immunogenic. As described herein, an immunogenic peptide that can be identified can be associated with disease in a patient. The HLA complex can be obtained endogenously from the patient. HLA complexes may comprise recombinantly produced HLA proteins and immunogenic peptides as described above. HLA complexes may comprise recombinantly produced HLA proteins and/or synthetically produced immunogenic peptides. Immunogenic peptides can be synthesized by standard methods. In certain embodiments, immunogenic peptides may be chemically synthesized by either manual or automated methods. In certain embodiments, immunogenic peptides can be synthesized by fluorenylmethoxycarbonyl protecting group chemistry.

Aspects of the present disclosure may further include synthesizing one or more identified peptides associated with the patient's disease. For example, where the disease is multiple sclerosis, such peptides may include peptides that form part of the myelin sheath that surrounds the axons of the individual's central nervous system. Alternatively, disease-associated peptides may include proteins common to most or all cell types. By way of example, such peptides may include cytoplasmic, cytoskeletal, nuclear, or membrane proteins.

A method of making a personalized biological filter may comprise binding HLA complexes to the inert filter surface of the biological filter. Consistent with disclosed embodiments, the filter may comprise an inert substance to which HLA complexes may bind. The term "inert" has been defined above. In some embodiments, filters may comprise one or more of polysulfones, polysulfone derivatives, glass matrices, silicon matrices, polydimethylsiloxanes, polycarbonates, polyetherimides, tritans, or combinations of the above or other materials. In another exemplary embodiment, the filter comprises polysulfone. The filter may further comprise a polyelectrolyte or any polymeric additive, alone or in combination with other materials identified above or other substances or materials. In other embodiments, the inert filter surface may comprise at least one of polyethylene glycol (PEG) or PEG derivatives, polystyrene, avidin or streptavidin. Alternatively, the surface of the filter may be somewhat or highly absorbent, or reactive with non-specific particles.

In certain embodiments, a filter can include multiple layers configured to allow fluid flow therebetween. Any layered structure, such as that described in FIG. 3, may be used as long as the fluid can contact a sufficient portion of the filtration medium to achieve the intended filtration function. good.

The HLA complexes may bind to the inert filter surface by any mechanism that allows the target T cell's TCR to bind to the HLA-peptide complexes. Binding can occur through adhesion, anchoring, chemical reaction, or any other mode of attachment of the HLA complex to the inert filter surface. For example, inert filter surfaces can be chemically designed to allow specific molecular and chemical properties to react with HLA complexes. HLA complexes can be placed on an inert filter surface by, for example, covalent bonding, non-covalent interactions, or adsorption. Examples of non-covalent interactions include, but are not limited to, electrostatic interactions, van der Waals forces, π effects, and hydrophobic effects. In certain embodiments, HLA complexes may bind to inert filter surfaces via analogues. As an example, HLA complexes can be placed on inert surfaces via maleimide analogues. In other embodiments, the HLA complex can be covalently attached to the surface of the filter via a maleimide analogue. In certain embodiments, HLA complexes can be introduced to an inert filter surface in an excess amount of solution to allow maximum saturation of the filter surface with HLA complexes. In certain embodiments, HLA complexes may be attached to inert filter surfaces via thiol bonds, disulfide bonds, amine bonds, or any other suitable functional group attachment. Alternatively, the HLA complex can be covalently attached to an inert filter surface, such as cysteine residues. Binding of HLA complexes to such inert filter surfaces is reflected in block 1818 of FIG. 18 as an example.

In some embodiments of the invention, the method of making a personalized biological filter can further comprise loading the identified peptides onto HLA complexes bound to the insert filter surface. Peptides can be loaded onto HLA proteins to form HLA-peptide complexes as previously described herein.

The timing of loading of identified peptides into HLA complexes and binding of HLA complexes to inert filter surfaces can be varied according to the requirements of a particular implementation. In some embodiments, loading and binding occur sequentially. That is, either the identified peptides are first loaded onto the HLA complex before binding to the inert surface material, or the HLA complex is first bound to the inert surface material and then the peptide is loaded. is either In other embodiments, loading and binding occur substantially simultaneously.

Individualized biological filters can be used to selectively remove pathogenic cells from patients. As noted above, removal of pathogenic cells from a patient can occur via any biological or chemical process. In some embodiments, this may involve flowing blood from the patient over HLA complexes bound to an inert filter surface, thereby trapping pathogenic cells. Pathogenic cells can be captured by HLA complexes bound to inert filter surfaces by any means involving binding, adhesion, or reaction with pathogenic cells. A personalized biological filter may be implemented by placing a stent coated with an HLA protein complex and inserting it into a blood vessel or anywhere in the body. Periodically the stent can be removed. A biological filter can be coated with streptavidin or any other chemical, and after infusion of biotin-conjugated HLA protein complexes into the blood, the specific binding of biotin-streptavidin removes the HLA complexes. To do so, connect the patient to the apheresis machine. As non-limiting examples, pathogenic cells can be associated with any one of the autoimmune diseases, cancers (solid tumors or hematologic cancers), and post-transplant complications disclosed herein. In one embodiment, the pathogenic cell is leukemia, acute leukemia, cancer, myasthenia gravis (MG), Lambert-Eaton syndrome, multiple sclerosis (MS), polycythemia vera (PC, PCV), thrombocytosis scleroderma, type 1 diabetes, psoriasis, Crohn's disease, or multiple sclerosis. In other embodiments of the invention, the biological filter can be used to trap pathogenic cells associated with at least one myeloproliferative disease or viral, bacterial, fungal or parasitic infections.
Methods of Treating Diseases in Patients

Some disclosed embodiments relate to treatment of patients and methods thereof. In some embodiments, treating a patient can refer to providing personalized medication or options to the patient. In some embodiments, patients can be treated for disease. For example, patients can be treated for various cancers, either hematological or solid cancers. Alternatively, in some embodiments, patients can be treated for autoimmune diseases. In connection with autoimmune diseases, treatment may involve downregulation of the patient's immune system. Alternatively, treatment of autoimmune diseases may involve targeting and removing one or more damaging agents from the patient's body. In some embodiments, the damage inducer can be a pathogenic cell. Note that although this disclosure provides examples of specific diseases for treatment, aspects of the disclosure in its broadest sense are not limited to specific diseases. Rather, the foregoing principles can be applied to any disease suitable for treatment of one or more of the altered mechanisms described herein.

Some embodiments of the present disclosure may involve identifying a patient's human leukocyte antigen (HLA) type. Suitable methods and techniques for HLA typing are described herein. In one embodiment of the present disclosure, identifying a patient's HLA type may simply involve taking a fluid sample from the patient and sending the fluid sample to a laboratory for HLA typing. In another embodiment, determining the patient's HLA type may comprise performing HLA typing on a fluid sample obtained from the patient. In any case, the ultimate goal is to obtain at least one, preferably many or all HLA types of the patient. As described herein, there are two types of HLA in the human body, HLA I and HLA II. Although there are thousands of HLAs in the population, humans each have 3 pairs of major HLAI types (A, B, C) and 5 pairs of type 2 (DP, DM, DO, DQ, DR) It has 6 HLA including By way of example, HLA typing can be performed using methods such as DNA sequencing, microlymphocyte toxicity assays, or hybridization of DNA to oligonucleotide probes, as described above. The above is provided as an example only with the understanding that embodiments of the present disclosure are not limited to any particular mechanism of identifying a patient's HLA type. Block 1902 of FIG. 19 therefore generally represents the step of identifying the patient's HLA type.

In some embodiments, identifying an individual's HLA type may comprise analyzing a blood sample taken from the individual. Alternatively, identifying an individual's HLA type may involve analyzing another biological fluid obtained from the patient. Some disclosed embodiments may involve identifying specific disease-associated peptides that cause activation of T-cell receptors in a patient along with the determined HLA type of the patient. Disease-associated peptides can be self-peptides, or non-foreign peptides specific to an individual, or foreign peptides that cross-react with self-peptides. As used herein, the term "self-peptide" generally refers to peptides produced from degradation of endogenously expressed proteins in the patient.

As used herein, the term "T cell receptor" (TCR) generally refers to a protein complex found on the surface of T cells. Due to genetic recombination, TCRs show remarkable diversity, and each type of T cell receptor recognizes a specific antigenic peptide bound to HLA. As used herein, the term "activation of the T cell receptor" generally refers to the binding of the T cell receptor to the HLA-peptide complex followed by other reactions of the immune system in vivo. Refers to the initiation of a signal cascade that activates a component.

Disease-associated peptides can be recognized by T cells of an individual's immune system and initiate an attack on the T cells. For example, disease-associated peptides can be presented by HLA-peptide complexes. In a further embodiment, the presented peptide can then be recognized by the T cell receptor, which can then bind the HLA-peptide complex. In some embodiments, the T cell receptor can only recognize specific peptides. Alternatively, a T cell receptor may recognize multiple peptides. In some embodiments, T cell recognition of specific peptides may result in one or more signaling. In further embodiments, T cell recognition and signaling of specific peptides may result in activation of T cells specific for those peptides. For example, activation of specific T cells can initiate a series of events including, but not limited to, T cell differentiation activation and clonal expansion. In certain diseases, T cells are activated by recognizing an individual's self-peptides, such that they migrate to and attack specific tissues within the individual.

Disease-associated peptides can be identified in a variety of ways. As will be appreciated by the inventors, determining the identity of one or more immunogenic peptides can be accomplished by, for example, procuring HLA-peptide complexes from a patient's biological fluid, extracting peptides from HLA proteins, Dissociating and analyzing the peptides using methods such as mass spectroscopy or Edman degradation may be included. Additionally, such peptides can be compared to a database of antigens to derive relevant information about the peptide. In some embodiments, the binding affinity of a peptide for a particular HLA is determined using methods such as, for example, surface plasmon resonance (SPR) or quartz crystal microbalance analysis (QCMA), electrochemical analysis, or biosensors. can be measured. Exemplary procedures involved in identifying disease-associated peptides are described above.

As noted above, disease-associated peptides may be associated with autoimmune disease, cancer, or any other disease involving an adaptive cellular immune response, including any one of autoimmune disease, cancer (solid tumors and hematological cancers), and It can be associated with various diseases such as the post-transplant complications disclosed herein. For example, disease-associated peptides can be associated with medical conditions involving either the patient's innate or adaptive immune response, including autoimmune diseases and cancer. Disease-associated peptides can be associated with the humoral or cellular arm of the adaptive immune response. For example, disease-associated peptides include leukemia, acute leukemia, myasthenia gravis (MG), Lambert-Eaton syndrome, multiple sclerosis (MS), polycythemia vera (PCV), thrombocytosis, scleroderma, 1 It can be associated with any one of autoimmune diseases, cancers (solid tumors and hematological cancers) and post-transplant complications, such as type diabetes, psoriasis, or Crohn's disease. In other embodiments, the disease-associated peptide may be associated with at least one of a myeloproliferative disease or a viral, bacterial, fungal or parasitic infection.

Consistent with some disclosed embodiments, identifying a particular disease-associated peptide includes identifying one or more immunogenic peptides and comparing them to a database of disease-associated immunogenic peptides and determined It may involve comparing their binding affinities to the patient's corresponding HLA types. Databases include, but are not limited to, information obtained from the literature or compiled based on testing of multiple individuals from linking peptides and their binding affinities to HLA from any source. information can be added. The database may be maintained locally, may be provided on a remote server accessed over a network, or may be provided by a third party in any manner. As mentioned above, bioinformatics and big data analysis can be used to predict which of the identified peptides have strong affinity to HLA previously identified from blood analysis. One example of a bioinformatics database that may be used in connection with embodiments of the present disclosure may include the IEDB database available via IEDB.org. Other examples are IMGT (imgt.org) and SYFPEITHI (syfpeithi.de). Such systems allow the user to interrogate to determine the binding affinity of a particular peptide for a particular HLA. Identifying specific disease-associated peptides by comparison to a database does not require access to the database in each instance. For example, a database may be pre-queried and a list of HLA-peptide affinities may be compiled such that direct access to the database is not required for each query. In this case, the compiled list can be considered its own database for the purposes of the embodiments of this disclosure.

In some embodiments, the database may be updated periodically based on data obtained from practicing medical professionals and their patients. For any given target patient, one or more disease-associated peptides can be identified, analyzed, or quantified. Embodiments of the present disclosure also include extracorporeal exposure of the patient's blood to filters treated with complexes composed of disease-associated peptides loaded onto the determined constructs of HLA, thereby generating HLA-peptide complexes. It may involve recognizing T cell receptors and causing binding of T cells to the filter. External exposure can involve any mechanism that treats blood outside the body. For example, it can be performed by drawing blood from an individual's vein and exposing the blood to a filter, regardless of the specific construction of the filter.

Filters to which blood is exposed can be treated so that selected proteins can be attached to desired surfaces through chemical reactions (or other mechanisms). A surface can be chemically engineered to impart specific molecular and chemical properties in order for it to react with proteins. Treatment or placement may occur when the surface is introduced to a solution containing the protein of interest, preferably in an excess amount that allows maximum saturation of the surface with the protein. By way of example, one or more of the exemplary filters described herein can be used for this purpose. In its broadest sense, some embodiments of the present disclosure are not limited to a particular mechanism of in vitro exposure, so in block 1906 of FIG. reflected without

Consistent with embodiments of the present disclosure, filters can be designed or configured to contain HLA-peptide complexes. For example, one or more immunogenic peptides associated with a disease may be attached to an HLA protein to form an HLA-peptide complex. In certain embodiments, HLA proteins may be recombinantly produced and peptides synthetically produced. For example, a DNA construct containing the HLA protein gene sequences can be inserted into a cellular expression system, which then expresses the HLA protein of interest. In another example, peptides can be synthesized by standard methods, including fluorenylmethoxycarbonyl protecting group chemistry. In other embodiments, both HLA proteins and peptides can be produced recombinantly using standard procedures. Alternatively, or additionally, HLA-peptide complexes can be obtained endogenously from an individual, such as a patient.

HLA proteins can be in any form, including monomers and/or multimers. As used herein, the term "monomer" generally refers to an HLA protein found in its natural state in a patient and which binds to a single peptide. As used herein, the term "multimer" generally refers to each monomer in a unit that can bind to one peptide and several to form a single unit. refers to the ligation of HLA monomers. As an example, each HLA monomer can be linked to a biotin molecule and mixed with streptavidin. Since each streptavidin molecule has four binding sites for biotin, a total of four biotinylated HLA monomers can be linked to streptavidin, thereby forming tetramers. In another embodiment, each HLA monomer is linked to an α-helix motif, and the individual α-helices each linked to an HLA monomer assemble to form a coiled-coil motif, thereby allowing multiple of HLA monomers can be linked to form multimers. In some embodiments, utilizing HLA multimers allows T cells to respond to HLA-peptide complexes because each HLA-peptide unit in the multimer can individually bind to T cell receptors on T cells. can increase the affinity of

As a schematic, the HLA-peptide pentamer is shown in Figure 20A. A pentamer is formed when α-helices 204 linked to HLA monomer 2006 bound to peptide 2008 assemble to form a coiled-coil motif. The pentamer can be further linked to a fluorophore 2002. FIG. 20B shows HLA-peptide tetramers. Tetramers are formed by linking a biotin molecule to each HLA-peptide complex and mixing the complex with streptavidin-2010.

In some embodiments, HLA proteins may include HLA I and/or HLA II proteins.

In some embodiments, the HLA-peptide complex can be linked to a detectable label. A detectable label can be a marker that allows the HLA complex or its components to be distinguished. Non-limiting examples of detectable labels include fluorophores, enzymes, radioisotopes, heavy metals, or nuclear magnetic resonance markers, or electrochemical labels. Such markers can bind to HLA proteins and/or peptides. In some embodiments, HLA-peptide complexes may be linked to more than one detectable label.

FIG. 21A shows a schematic representation of HLA I protein 2102 linked to fluorophore 2104. FIG. FIG. 21B shows HLA II protein 2106 linked to enzyme 2110 via peptide linker 2108. FIG.

Aspects of the present disclosure may include returning bound T cells to the patient's blood in a depleted state. References to blood returned to a patient may include any or all components of the returned blood. For example, after blood is extracted from a patient for treatment, the blood components can be separated and some can be returned to the patient and others not. As used herein, returning blood to the patient encompasses both scenarios. As discussed elsewhere herein, the blood may be processed in stages and the blood separated blood components may be recombined and returned to the patient at the same time. Alternatively, blood components can be returned continuously. In its broadest sense, embodiments of the present disclosure are not limited to specific timings or specific groups of blood components returned into the patient, so long as some components are eventually returned. Thus, block 1908 of FIG. 19 generally refers to returning bound T cells to the patient's blood in a depleted state.

In some embodiments, depleted T cells may include cytotoxic T cells, helper T cells, or memory T cells. For example, depleted T cells can include CD4+ or CD8+ T cells, or both. In some embodiments, the patient's blood can be enriched with materials before being returned to the patient. For example, the material may be a nutraceutical or pharmaceutical composition, or both.

The disclosed methods of extracorporeal filtration and removal of bound T cells can be performed on a patient one or more times during a given year. In certain embodiments, the process may be performed on the patient several times during a given year, depending on the patient's needs.

In some embodiments, a filter containing bound T cells can be subjected to a standard separation agent to allow the bound T cells to be separated from the filter. In certain embodiments, depleted T cells can be counted. By way of example, separation of bound T cells can be performed via physical, chemical, or biological means. In preferred embodiments, the separation method cannot damage the separated T cells or filters. Any suitable detachment agent may be used to remove bound T cells. In some embodiments, T cells can be counted via fluorescence activated cell sorting (FACS). In general, any suitable method for counting T cells can be used.

As a schematic, FIG. 22A shows how T cells 2202 are removed from HLA-peptide complexes 2204 placed on filter 2206. FIG. Figure 22B shows a schematic of the FACS process.

In certain embodiments, the number of T cells counted can be used to estimate the progression of certain diseases that are dependent on specific T cell numbers. For example, if a serial count showed a decrease in the number of T cells counted, such a trend could indicate that the disease is in remission. In some embodiments, the number of T cells counted can be used to determine how best to treat a patient suffering from a particular disease. As an example, the number of T cells counted can be used to alter patient therapy, eg, by altering the design of subsequent filters used with the patient.

Consistent with this disclosure, an anticoagulant may be administered to the patient. The term "anticoagulant" generally refers to an anticoagulant or any agent that helps prevent blood from clotting. Generally, any suitable anticoagulant can be administered to the patient.
Methods for treating patients with T cell-associated autoimmune diseases

The present disclosure relates to methods of treating patients with T cell-associated autoimmune diseases. This is done by predicting that as a disease caused by activated T cells progresses, one or more T cell populations that have not yet caused the disease will likely cause the disease in the future. can be actively involved. Additions not already causing this disease, if predicted based on known data and affinities of certain peptides for certain human leukocyte antigen (HLA) proteins and other proteins with similar characteristics of T cells can be removed before they cause problems. An example of such a process is reflected schematically in FIG. This and other examples are discussed in more detail below.

Note that although the present disclosure provides examples of methods of treating T cell-associated autoimmune diseases, aspects of the disclosure in its broadest sense are not limited to T cell-associated autoimmune diseases. Rather, the aforementioned principles can also be applied to treat other diseases.

The term "treatment" refers to the performance of a process in an attempt to improve a patient's medical condition. Consistent with some disclosed embodiments, this may include providing personalized medicine to patients suffering from T-cell related autoimmune diseases.

Consistent with disclosed embodiments, a method of treating a patient with a T cell-associated autoimmune disease may include treating a patient with multiple sclerosis, wherein the T cell is a myelin or aquaporin channel It can be activated against non-myelinating central nervous system proteins, including Multiple sclerosis is a T cell-associated autoimmune disease in which T cells can activate and attack proteins in the central nervous system, resulting in a wide variety of neurological symptoms. Activation occurs when T cell receptors on T cells recognize peptides derived from central nervous system proteins. When a T cell receptor encounters a peptide, the T cell undergoes an activation process that migrates to the central nervous system and initiates an immune response. In some cases, T cells are activated toward myelin, resulting in demyelinating processes in the brain and spinal cord. Myelin is a protective sheath that surrounds nerve fibers in the brain, optic nerve, and spinal cord. When the myelin sheath is damaged by these activated T cells, nerve impulses slow or stop, causing neurological problems. In some embodiments, the myelin comprises myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), myelin proteolipid protein (PLP), opaline protein, oligodendrocyte specific protein (OSP), It may comprise one or more myelin-associated glycoproteins (MAG), or combinations thereof, or other myelin-associated proteins. Aquaporin channels, sometimes called aquaporins or water channels, are integral membrane proteins derived from a large family of major intrinsic proteins that form pores in the membranes of living cells and primarily facilitate the transport of water between cells. is.

Consistent with some embodiments, a method of treating a patient with a T cell autoimmune disease may comprise obtaining HLA-peptide complex data for a particular patient with the autoimmune disease. The term "human leukocyte antigen" (HLA) generally refers to a system or complex of proteins encoded by an individual's major histocompatibility (MHC) gene complex. HLA proteins are typically found on the surface of human cells, involved in the regulation of an individual's immune system. For example, HLA proteins can function by recognizing foreign, non-self materials within an individual and initiating an immune response that neutralizes those materials.

"HLA-peptide complex data" can refer to the characterization of some or all of the peptides presented by specific alleles of HLA proteins from a patient. Each peptide has a different binding affinity for a particular HLA protein.

HLA-peptide complex data can be obtained through analysis of a particular patient's HLA-peptide complexes and can include determining the amount of HLA-peptide complexes in a particular patient. Accordingly, "acquire" as reflected in box 2312 of FIG. It can contain one or more. Quantitative analysis of patient HLA-peptide complex data can involve the construction of single-type HLA protein lines, each loaded on a different peptide. An HLA protein can consist of 1-100 different myelin or non-myelin peptides separately loaded onto the HLA protein. 10-100 ml of human peripheral blood mononuclear cells (PBMC) from a patient can be stained with a fluorescent marker such as carboxyfluorescein succinimidyl ester (CSFE). After washing the markers from the cells, the PBMC can be incubated with surface-anchored HLA proteins for 15-40 minutes. After washing the PBMC from the surface, quantification of the number of cells in each complex with different HLH can be measured by the intensity of fluorescence units. Quantitation can be measured by any other method, such as photoreaction. Quantitative analysis of HLA-peptide complex data can also include direct analysis of stripped peptides removed from the patient's antigen presenting cells (APCs). Stripping can be performed by mixing PBMC with acid solutions for various times, resulting in a stripping reaction of peptides loaded onto the HLA groove. Peptides can then be harvested for mass spectrometry to determine the sequence or quantity of the peptide.

Obtaining HLA-peptide complex data for a particular patient can include analysis of HLA typing and related peptides. HLA typing can be determined via at least one of blood analysis and peptide analysis via at least one of cerebrospinal fluid (CSF) analysis or tissue-specific disease-associated peptide analysis be able to. More specifically, analyzing relevant peptides can include examining the cerebrospinal fluid of a particular patient. Stripping analysis can be performed from cerebrospinal fluid (CSF).

As used herein, the term "blood analysis" can refer to analyzing whole blood or a fraction of whole blood. Blood fractions can refer to smaller, specific blood components. In some embodiments, a blood fraction may include plasma, white blood cells, red blood cells, serum, or any other specific component of blood. As used herein, "cerebrospinal fluid (CSF)" refers to the clear, colorless fluid found in the brain and spinal cord.

Blood, cerebrospinal fluid, or other tissue-specific samples can be obtained from the patient and analyzed. For example, analysis of related peptides can include stripping peptides from HLA complexes and determining peptide sequences. Peptides can be removed from the HLA complex by any suitable means. In some embodiments, peptides can be removed from HLA complexes by chemical means. Sequencing of peptides, which includes identifying the amino acid composition and order of peptides, can be performed by means well known in the art. Once such data about a patient is collected, it can be stored in a record and then retrieved for the purposes of practicing methods consistent with this disclosure.

In connection with some embodiments of the present disclosure, the (HLA)-peptide complex data obtained in patients with an autoimmune disease induced by a first T cell and not a second T cell can be related. In T-cell-associated autoimmune diseases, one T-cell subtype is activated in the early stages of the disease, whereas a second T-cell subtype may be activated in the later stages of the disease. These secondary T-cell subtypes are later activated as a result of early attack by the first T-cell subtype, exposing more protein structures and recruiting the second T-cell subtype. obtain. As a non-limiting example, in a comparison of two patients with identical HLA typing, the first patient was a newly diagnosed patient and the second patient was a more advanced patient with more advanced disease. Patients are assumed to have more activated T cell subtypes that cause disease.

In certain embodiments, a method of treating a patient may include identifying additional T cell populations that may cause autoimmune disease over time. For example, HLA typing and related peptide analysis can be used to identify additional T-cell populations to predict disease progression (e.g., not currently causing disease, but may cause disease in the future). identify the T cell populations expected to elicit). Certain primary T-cell subtypes may be associated with early stages of disease and secondary T-cell subtypes may be associated with late stages of disease, but autoimmune Disease need not be limited to two related T-cell subtypes. Historical analysis of data from patients with similar HLA typing and peptide analysis would allow identification of more than two T cell subtypes.

Once the HLA-peptide complexes are obtained for a particular patient, the method of treating the patient is to combine the HLA-peptide complex data of the particular patient with the HLA-peptide complexes associated with a population of patients with T cell-related pathologies. data, wherein the population data show that individuals with an autoimmune disease induced by a first T cell progress over time to become induced by a second T cell. Contains suggestive epitope spreading information. Such a comparison is reflected as an example of block 2314 in FIG. Because autoimmune diseases have unique T-cell-associated pathologies, patients with the same autoimmune disease may have similar T-cell-associated pathologies throughout the course of the disease. As a further example, comparing HLA-peptide complex data between specific patient data and population data can include comparing patients sharing each other's HLA types. Population data can be collected over time from databases that track HLA association analyzes from populations. Such information can be stored in a database and made accessible to the relevant medical community. With access to this data, physicians can predict how T-cell activation will evolve in a particular patient.

More specifically, comparing HLA-peptide complex data for a particular patient with HLA-peptide complex data associated with a patient population with T-cell-related pathology may be useful in determining age from onset, symptoms, and treatment, comparison of disease-related parameters, HLA typing analysis, and analysis of peptides presented by corresponding HLA proteins. Determine how autoimmune disease progresses for a given patient by comparing HLA-peptide complex data from a given patient with population data from patients with similar T cell-associated pathology and predict future epitope spread for a given patient.

The term "epitope spreading" generally refers to the diversification of epitope specificity beyond the initial immune response. Autoimmune diseases may have unique epitopes against which the initial immune response is directed, but target epitopes may spread and diversify to other targets as the disease progresses. This epitope spreading information can be included in population HLA-peptide complex data for specific autoimmune diseases. The time and rate of epitope spreading varies between autoimmune diseases and patient populations and can include days, weeks, months or years. In populations with certain autoimmune diseases or HLA-peptide complexes, epitope spreading can be intramolecular or intermolecular. Intramolecular spreading involves spreading epitopes to other sites on the same antigen. Intermolecular epitope spreading includes spreading of epitopes to other antigens. Epitope spreading information within the population HLA-peptide complex data was analyzed over time as patients with autoimmune diseases induced by the first T cell were induced by a second T cell or additional T cells. May suggest whether to proceed. Such identification of expected epitope spreading is reflected in block 2316 of FIG. 23 as an example.

In some embodiments, the method includes removing a second T cell (or additional T cells) from a particular patient before an autoimmune disease in the particular patient is induced by the second T cell (or additional (T cells of the body). Removal of second T cells or additional T cells can be accomplished by any means available for separating second T cells from biological material. Some non-limiting examples are provided herein using biological filters to trap disease-inducing T cells. In these instances, the patient's blood can be filtered not only for T cells that are currently causing disease, but also for T cells that are expected to cause disease in the future as the disease progresses. Such proactive removal is reflected in block 2318 of FIG. 23, as an example.

FIG. 24 shows an exemplary process of removing secondary T cells prior to causing autoimmune disease. As illustrated, at node 2412, after the disease is activated by the first type of T cells, epitopes diffused at 2414 cause activation and recruitment of the second type of T cells at node 2416. . These secondary T cells can induce or exacerbate autoimmune responses in patients. However, before the second T cells trigger the patient's autoimmune response at node 2420, they are removed from the patient at node 2418.

Depletion of the second T cell can include binding of the HLA-peptide complex to the T cell receptor of the second T cell. Similarly, removal of additional T cells can include binding of HLA-peptide complexes to the T cell receptor of additional T cells.

In some embodiments, the second T cells and additional T cells are removed by a biological filter as described herein. Filters can be constructed to remove specific types or subpopulations of T cells, or multiple types of T cells. For example, one filter may bind multiple HLA complexes to remove multiple types of T cells. For example, in Figures 12A-12D, the biological filters may contain different HLA complexes on a single filter for binding different T cells. Alternatively, filters may be specific for particular T cells. In such embodiments, leukocytes can be serially cycled through multiple filters to remove multiple types of T cells during a single treatment. Thus, for example, in FIGS. 12A-12D, two or more filters 1016 may be arranged in series with a recirculation loop 1024 that recirculates leukocytes from the furthest downstream filter outlet to the furthest upstream filter inlet. Alternatively, a patient can receive multiple treatments, each with different filters to deplete different T cells.

A method of treating a patient may further comprise adjusting treatment based on the identified second T cells and/or additional T cells. The aforementioned term "treatment", particularly in this context, can refer to the process of removing pathogenic T cells from the blood. For example, it can generally refer to a process designed to deplete, or at least reduce the amount of, diseased cells or cell fragments in a patient. Adjustments to treatment may include adapting the pathogenic T cell elimination process to facilitate elimination of identified second and/or additional T cells. This involves modifying biological filters to contain HLA-peptide complexes designed to bind to T-cell receptors on secondary and/or additional T-cells to remove them from the blood or Modification can be included. Modulation of treatment may alternatively or additionally include the implementation of other treatment options such as administration of pharmaceuticals or biologics, plasmapheresis, and/or physical therapy.

In some embodiments, the method of treating a patient comprises removing a second T cell prior to inducing or exacerbating an autoimmune disease in the patient, although in some embodiments the method comprises the treatment of the first removing the T cells of the first and the second T cells at the same time. Similarly, the method can involve depleting the first T cell and the additional T cells simultaneously. Embodiments of the present disclosure can be used to treat patients with autoimmune diseases induced by second T cells or additional T cells by removing these T cells from the patient, although the first 1 T cells can also induce autoimmune disease in patients. Therefore, it may be beneficial to remove the first T cell at the same time as the second or additional T cells. Depletion of the first T cell can be accomplished using similar means as depletion of the second or additional T cells. For example, elimination of the first T cell can involve binding of the HLA-peptide complex to the T cell receptor of the first T cell. Additionally, the first T cells can be removed by a biological filter.
Methods for estimating pathogenic T cell numbers in mammals

In situations such as in the process of tracking disease progression, or as part of the process of creating a biological filter, it can be useful to estimate the amount of disease-specific pathogenic T cells in a patient. A general knowledge of the amount of disease-triggering T cells helps design biological filters to remove T cells. And by knowing roughly how many pathogenic T cells are in the body at a given time, the progression of the disease can be tracked. An increase in pathogenic T cells tends to indicate progression of the disease and a decrease tends to indicate remission. To this end, some embodiments of the disclosure include methods of estimating the amount of disease-specific pathogenic T cells in a patient. As used herein, the term "estimate" in estimating disease-specific pathogenic T-cell numbers ranges from categorical estimates (e.g., minimal, low, moderate, high, very high) to roughly Predictions ranging from estimates (eg, rough numerical estimates) to more precise numerical estimates may be included. Estimates may be based on color changes, brightness levels, or intensity of color as produced by assay or marker use. Estimation may be based on procedures such as fluoroscopy or cell counting (eg, via machine vision techniques). Estimates may be based on ex vitro evaluation of samples taken from patients. Such samples may include blood, cerebrospinal fluid, or any other biological fluid or substance. Estimates can, by way of example, reflect a patient or a large number of T-cells, including various T-cell subtypes in a patient; ) with specific HLA loaded with disease-specific proteins and peptides. Incubation of these two components (PBMC and HLA protein complex) can attract specific T cell subtypes present in the biological fluid or material.

According to embodiments of the present disclosure, a method of estimating the amount of disease-specific pathogenic T cells in a patient may comprise obtaining a first biological fluid sample from the patient. Non-limiting examples of biological fluids include whole blood, serum, plasma, cerebrospinal fluid, synovial fluid, alveolar lavage, pancreatic juice, gastrointestinal lavage, peritoneal lavage, lymph, bone marrow, amniotic fluid, semen, pleural effusion, breast milk, heart. There is membrane fluid, saliva, feces, bile, and urine.

Obtaining a biological fluid from a patient can include, for example, aspiration and/or drainage through a device such as a needle or catheter that can be connected to a collection container or tubing set. Such methods and techniques can be used with biological fluids such as whole blood, cerebrospinal fluid, synovial fluid, alveolar lavage, peritoneal lavage, lymph, or bone marrow. However, biological fluids such as gastrointestinal lavage and urine can be obtained non-invasively by sampling as the fluid is excreted from the body. Embodiments of the present disclosure, in its broadest sense, are not limited to particular methods of obtaining particular types of biological fluids or biological fluid samples. Thus, although block 2502 in exemplary method 2500 of FIG. 25 indicates that samples are obtained, it is not so limiting. For example, a sample can be obtained simply by receiving it from another person who took the sample.

A patient with an estimated number of disease-specific pathogenic T cells may be suffering from an autoimmune disease, cancer, or a post-transplantation complication or condition described herein. Examples include multiple sclerosis, type 1 diabetes, myasthenia gravis, Crohn's disease, and the like. Since the purpose behind obtaining biofluids is to identify disease-specific or antigenic peptides recognized by pathogenic T cells, biofluids localized to pathological sites, or pathological It may be desirable to obtain biofluid in the vicinity of the site (eg, within 10-20 mm of the pathological site). For example, if the patient is a multiple sclerosis patient whose central nervous system is compromised, a suitable biological fluid of choice may be, but is not limited to, cerebrospinal fluid. If the patient has Crohn's disease that affects the intestinal system, a suitable biological fluid to choose is gastrointestinal lavage, but is not limited thereto.

In disclosed embodiments, it can further comprise stripping native peptides from the first group of human leukocyte antigens (HLA) in the first biological fluid sample. Stripping of native peptides bound to a patient's HLA can be accomplished using protein chemistry techniques such as altering the pH value of biological fluids to disrupt the interaction between peptides and HLA, or peptides using agents such as DMSO. It can be achieved by several different methods, including denaturation. By way of example, after a biological fluid sample is obtained from a patient, cells in the sample can be separated, eg, by centrifugation, after which the cell fraction can be collected as a pellet. The harvested cell fraction can be reconstituted in a suitable buffer prior to lysis. Various techniques such as mechanical disruption (e.g. French press), liquid homogenization, high frequency sonication (e.g. sonication), freeze/thaw cycles and manual grinding, and chemical lysis (e.g. sodium dodecyl sulfate or SDS). Cell lysis techniques can be used. Cell lysis procedures can result in disruption of cell membranes to release intracellular proteins, including native peptides bound to HLA.

The HLA-native peptide complex can then be isolated from the protein pool using techniques such as Fast Protein Liquid Chromatography (FPLC), High Performance Liquid Chromatography (HPLC), where the protein mixture are fractionated into individual proteins based on properties such as polarity, charge, hydrophobicity, molecular weight or affinity for a particular ligand. Alternatively, HLA-native peptide complexes may be isolated using immunoprecipitation. Immunoprecipitation can be performed, for example, by introducing protein mixture antibodies known to bind HLA complexes. Such antibodies include, for example, anti-HLA antibodies, anti-HLA type I antibodies (A, B and C), anti-HLA type I A antibodies, anti-HLA type II antibodies (DR, DP, DQ), anti-HLA DR antibodies , anti-HLA DRb15:01 antibodies, and other antibodies that promote immunoprecipitation. Immunoprecipitation thus results in separation of a mixture of different HLAs and different bound native peptides from the rest of the proteins and peptides released from the cell.

Removal of native peptides from HLA can be selectively performed to preserve the integrity of HLA for later use in the method, e.g., interactions between peptides and HLA may affect the chemical properties of peptides. Due to changes in properties, not only HLA is destroyed due to changes in chemical properties of peptides, only HLA is denatured, but HLA is not denatured. Alternatively, removal of peptides from HLA can be done universally, with subsequent restoration of the original properties of HLA. Removal of native peptides from HLA can result in a mixture of pathogenic and non-pathogenic peptides. As generally reflected in block 2504 of FIG. 25, native peptides may be removed from HLA. Stripping in block 2504 is not limited to any particular process, as there are many methods for stripping peptides from HLA and the present disclosure is not limited to any particular process.

Some disclosed embodiments may involve determining the sequence of one or more of the stripped native peptides. The sequences of native peptides removed from HLA can be determined using protein sequencers (sequencers) by peptide sequencing techniques such as mass spectrometry and Edman degradation. Sequencing can yield a unique code or identifier for each peptide. In other embodiments, HLA-peptide complexes may be endogenously derived from the patient. In its broadest sense, the disclosed embodiments are not limited to any particular method of performing sequencing. Accordingly, determining one or more sequences in block 2506 of FIG. 25 is not limited to a particular sequencing method. In fact, one or more of sequencing as used herein involves sending samples to a clinical laboratory that returns sequencing results, regardless of the process used in the lab. Typically, but not necessarily, many different peptides can be removed from the HLA and their sequences determined.

In some disclosed embodiments, comparing the determined one or more sequences to known information can be included to determine one or more disease-specific peptide sequences among the native peptides. . A peptide having a "disease-specific sequence" refers to any peptide, presently known or not, that affects disease. Such peptides may already be known to influence disease, and knowledge of their influence may be identified in the future through bioinformatics and other analyses. Furthermore, peptides with disease-specific sequences include peptides whose sequence is unknown but subsequently determined. As noted above, each peptide may have its own unique sequence, reflected, for example, as a code or other identifier. The sequence of the native peptide can then be compared with known information. As used herein, "known information" can include any data that reflects previously determined structure or relationships. For example, bioinformatics and big data analysis can be used to compare sequenced natural peptides to peptide sequences already known to correlate with disease.

For example, such analyzes may include known reference sequences associated with proteins associated with disease (e.g., myelin-associated proteins in the case of multiple sclerosis), or disease symptoms known to be associated with the sequences. Other information, such as, can be compared to native peptides. To determine one or more disease-specific peptide sequences among the native peptides, NCBI BLAST (https://blast ncbi.nlm.nih.gov/Blast.cgi) or any other algorithms and programs for comparing primary biological sequence information can be used. These sources may include protein or peptide amino acid sequences. Matches can be determined by comparing one or more query amino acid sequences to a library or database of reference amino acid sequences and identifying those library sequences that are similar to the query sequence above a certain threshold. As used herein, the term "reference sequence" refers to the biological sequence information of known disease-specific peptides. Block 2508 of FIG. 25 generally presents a comparison of the determined sequence of the native peptide to known information. Block 2508 does not specify a particular method, as there are many ways to do the comparison, as described above. In its broadest sense, comparison can be performed by sending the determined sequences to a third party for analysis.

Some disclosed embodiments load HLA onto a second group of peptides that share one or more disease-specific peptide sequences to form multiple HLA-peptide complexes. can include A peptide having a "disease-specific sequence" refers to any peptide, presently known or not, that affects disease. Such peptides may already be known to influence disease, and knowledge of their influence may be identified in the future through bioinformatics and other analyses. Furthermore, peptides with disease-specific sequences include peptides whose sequence is unknown but subsequently determined. A loaded peptide may be selected, for example, as the top pathogenic peptide determined during the aforementioned comparison process. The methods and techniques involved in loading peptides into HLA are described herein and are not mentioned again to avoid repetition. The second group of HLA's may be the same as the first group or may be a different group. Copies of loaded disease-specific peptides can be produced recombinantly using molecular biology methods and techniques. In some embodiments, an HLA-peptide complex may comprise multiple synthetically or recombinantly produced/engineered peptides that share one or more disease-specific sequences. In other embodiments, the HLA-peptide complex can be obtained endogenously from the patient. In its broadest sense, the disclosed embodiments are not limited to any particular mechanism of loading peptides into HLA. Accordingly, in block 2510 of FIG. 25, loading is generally indicated without reference to a particular loading mechanism.

In some disclosed embodiments, it can further include contacting a plurality of HLA-peptide complexes with a second biological fluid sample. For example, the HLA-peptide complexes can be bound or otherwise deposited on a medium, such as one or more test strips or surfaces, where each different HLA-peptide complex is located in a separate area. . Biological material such as blood, cerebrospinal fluid, or any other material disclosed herein can be stained on the test area. Alternatively, a biological fluid may be flowed over the test area. This allows T cell receptors in the biological material to bind to the HLA-peptide complexes in the test area. The amount of T cells that bind can be a function of the binding affinity of a particular T cell to a particular HLA-peptide complex. Since biological samples can be contacted with HLA-peptide complexes in a variety of ways, 2512 in Figure 25 generally refers to contacting without specifying a particular contacting method. In the broadest sense, contacting can be referred to a clinical laboratory consistent with the meaning of the phrase "contacting" as used herein.

The disclosed embodiments can also include determining, for the plurality of HLA-peptide complexes contacted with the second biological fluid sample, the amount of T cells that bind to the plurality of HLA-peptide complexes. As mentioned above, the binding affinity of HLA-peptide complexes for T cell receptors can be revealed by the amount of T cells that bind to a particular HLA-peptide complex test area. The amount of T cells that bind to each area can be quantified in various ways. Cells can be counted for more precise quantification and markers can generally be used to indicate the amount of bound T cells by color indicator or intensity measurement. Many methods of quantifying the amount of cells are available, so block 2514 of FIG. 25 generally refers to the determination without specifying a particular mechanism. In the broadest sense, judgment only requires sending material to a third party for analysis.

In some embodiments, based on the amount of identified T cells that bind multiple HLA-peptide complexes, the amount of disease-specific pathogenic T cells can be estimated in a biofluid volume within a patient. . For example, in a general sense, the amount of bound T cells on the aforementioned test area can be used as a general indicator of the amount of disease-specific T cells in the patient's blood, cerebrospinal fluid, or other bodily fluids or substances. can help. As used herein, estimation includes both categorical estimation and numerical estimation. Classification estimates include indicators such as high and low values. Numerical estimation can provide estimated quantifications such as numbers and volumes. Such estimates can be derived from the amount of T cells detected in the test area. The amount can be extended by estimating the amount of T cells in the patient's biofluid volume through correlation. In general, estimation is reflected in block 2516 of FIG. 25, covering all forms of classification and numerical estimation, regardless of how they are performed. Sending material to a third party who performs part or all of the process of estimation is within the scope of estimation as used herein.

In some disclosed embodiments, a given amount of T cells that bind multiple HLA-peptide complexes have multiple peptides that share one or more disease-specific peptide sequences. In another embodiment, the amount of T cells that bind multiple HLA-peptide complexes comprises multiple peptides that share multiple disease-specific peptide sequences.

The disclosed embodiments can also include HLA that can be linked to detectable markers to be detected and quantified. Examples of suitable detectable markers include at least one of fluorophores, enzymes, radioisotopes, heavy metals, and nuclear magnetic resonance markers.

Methods for estimating the amount of disease-specific pathogenic T cells in a patient can also be varied by incorporating one or more steps in addition to the steps described above. For example, using bioinformatics and big data analysis such as the "Immune Epitope Database and Analysis Resource" (iedb.org), among the determined disease-specific peptides, isolated and identified in patient biofluid samples It is possible to predict those with strong affinity to HLA of a specific peptide and determine the binding affinity of a specific peptide to a particular HLA. A list of disease-specific peptides predicted to have strong affinities for a patient's HLA, and their respective predicted binding affinities, are identified for specific HLA peptide pairs and/or for HLA and Different combinations of disease-specific peptides can be generated. When constructing a biological filter as discussed further below, one can focus on HLA-peptide complexes with binding affinities above a threshold (eg, the top 10 HLA-peptide complexes). Thus, an exemplary method for estimating the amount of disease-specific pathogenic T cells includes, prior to determining the amount of T cells that bind to multiple HLA-peptide complexes, multiple It may further comprise measuring, estimating or predicting the binding affinity of each of the HLA-peptide complexes. Measurement or estimation of actual binding affinity can be done using techniques such as surface plasmon resonance (SPR) and quartz crystal microbalance analysis (QCMA), or sensors based on the QCMA concept or enzyme-linked immunosorbent assay (ELISA). can be done.

Another exemplary method of estimating the amount of disease-specific pathogenic T cells can further comprise verifying that disease-specific pathogenic T cells bind to multiple HLA-peptide complexes. Validation can be, for example, by removing bound disease-specific peptides from the HLA-peptide complex and sequencing the peptides (most accurate), or by assessing the molecular weight of bound disease-specific peptides (e.g., by mass spectrometry , light scattering techniques (SLS, MALS) or SDS-PAGE electrophoresis), by comparing the determined molecular weight to the known molecular weight of the correct disease-specific peptide.

According to some disclosed embodiments, the method of estimating the amount of disease-specific pathogenic T cells further comprises, based on the estimated amount of disease-specific pathogenic T cells, the patient's disease progression, It may include an assessment of condition or status, or an assessment of the efficacy of a therapeutic regimen, or an assessment of how well a patient is responding to a therapeutic regimen. As an example, a method of estimating the amount of disease-specific pathogenic T cells further includes assessing the disease state based on the determined amount of T cells that bind to multiple HLA-peptide complexes. can be In one embodiment, assessing the disease state compares the determined amount of T cells that bind the plurality of HLA-peptide complexes to the amount of T cells determined from a population of patients with the disease. can include Another exemplary method for estimating the abundance of disease-specific pathogenic T cells includes the determined amount of T cells that bind multiple HLA-peptide complexes and the amount of T cells that bind multiple HLA-peptide complexes. Evaluating the efficacy of the therapeutic regimen for the disease by comparing the amount of T cells determined in the method. Such an assessment is beneficial in that treatment regimens can be tailored according to patient needs. For example, if the amount of T cells bound to HLA-peptide complexes is not decreasing, the therapeutic regimen can be adjusted by increasing the dose of the drug or by changing to an entirely new therapeutic regimen. Alternatively, if the amount of T cells bound to HLA-peptide complexes is successfully reduced, the dose of drug can be reduced or the treatment regimen can be discontinued altogether. Accordingly, some disclosed embodiments provide a determined amount of T cells that bind multiple HLA-peptide complexes and a previously determined amount of T cells that bind multiple HLA-peptide complexes. adjusting the treatment regimen based on the comparison.

In yet another example, the method of estimating the amount of disease-specific pathogenic T cells can further comprise creating a biological filter comprising a plurality of HLA-peptide complexes. Making a biological filter can involve synthesizing a plurality of peptides that share one or more disease-specific sequences, eg, using techniques described herein. Making a biological filter includes, for example, a step of synthesizing HLA, mixing the synthesized HLA with a plurality of synthesized peptides that share one or more disease-specific sequences to form a synthetic HLA- The steps of forming a peptide complex and applying the synthetic HLA-peptide complex to the inert surface medium of a biological filter can further be included. The methods and techniques involved in applying or anchoring HLA-peptide complexes to the inert surface media of biological filters are described above. As described above, different HLA-peptide combinations that trap T cells can be identified and their binding affinities can be measured, estimated or predicted. Based on binding affinities, HLA-peptide complexes with the highest binding affinities for disease-specific pathogenic T cells can be synthesized and incorporated into filters.

In certain embodiments, a test kit may be provided prior to fabricating the biological filter. A test kit may comprise a test strip, wherein each HLA-peptide complex (all different combinations) may be immobilized on a different area of a test surface (or different test surface) such as glass or silicon. good. Preferably, only one HLA-peptide complex type can be anchored to each surface region or part of the surface so that each region can contain a unique HLA-peptide complex. This allows testing of the HLA-peptide complexes most relevant to a particular patient. Biological fluids such as blood can be used to stain each region and trigger binding of T cells to the relevant HLA-peptide complexes. T cells bound to each area can then be counted or estimated using, for example, an automated spectrophotometer reader.

As noted above, the methods and systems of the present disclosure can be used to treat diseases, including autoimmune diseases, cancer, and post-transplant complications or conditions, including one of these diseases and conditions disclosed herein. It can be used in patients with a number of diseases, including: In certain embodiments, the patient may have multiple sclerosis and the one or more disease-specific peptide sequences are those of peptides derived from myelin-associated proteins. In another embodiment, the patient may have type 1 diabetes and the one or more disease-specific peptide sequences may be those of insulin peptides, or other proteins associated with beta-cell proteins. The patient may have myasthenia gravis and the one or more disease-specific peptide sequences may be that of an acetylcholine receptor peptide. In another embodiment, the patient may have Crohn's disease and the one or more disease-specific peptide sequences may be derived from the liver, pancreas, colon, rectum, stomach, gallbladder, or small and large intestine. It can be an array.

Summary of Examples 1-7 The experiments described in Examples 1-7 are a proof of concept in a multiple sclerosis (MS) mouse model, namely demyelination from various leukocyte extracts in solution. It was designed to demonstrate the protein's ability to recognize and trap specific populations of triggering T cells and to be able to measure the quality of such isolation. FIG. 27 shows the percentage of stained right upper quadrant (RUQ) T cells recognizing the peptide MOG, which was 5.15%. This fraction represents a relatively small number of T cells with receptors recognizing the peptide MOG. Under normal conditions, one T cell clone constitutes a small fraction of the total T cell population (Lythe et al.J. Theor.Biol., 2016, 389:214-224). However, the presence of MOG in the proliferation assay allowed us to receive a higher percentage of T cells that recognized MOG, resulting in a percentage of 5.15% in FIG.

Following the recognition and separation procedure, there was an opposite trend, namely a decrease in the proportion of specific T cells in the mixture of cells that did not bind the protein complex (commercially available HLA tetramer) and, in contrast, these There was an increase in the proportion of these specific harmful T cells in the cell population that bound the protein complex of . These results are shown in Figures 28A, 28B and 29A, 29B. RUQ significantly decreased from 5.15% to 0.77% and 0.56% in Figures 28A and 28B. In contrast, in 29A and 29B examining cell populations within the figure columns, the percentage of specific T cells within the columns after the initial separation was 5.82% (see Figure 29A RUQ). This number is very close to the percentage obtained in Figure 27 (5.15%), indicating that even a single isolation yielded the total amount of harmful T cells and that the formed protein-T cells were stable. Proven. This set of results demonstrates that the proteins used in this method recognize and capture specific T cells from various cell populations with very high efficiency. This result demonstrates that the proteins used in this method are highly specific and efficient in recognizing and trapping specific pathogenic T cells from various leukocyte populations. This specific depletion of T cells prevented experimental autoimmune encephalomyelitis in the treatment group.
Example 1: Induction of Experimental Autoimmune Encephalomyelitis (EAE) in Mice

An experimental autoimmune encephalomyelitis (EAE) model in mice. Autoimmune encephalitis in mice is widely used as an animal model to mimic multiple sclerosis in humans. Autoimmune encephalitis was induced by injecting six 6- to 7-week-old mice with a myelin component called MOG emulsified in complete Freund's adjuvant and pertussis toxin administered on the day of induction and 48 hours later. Injection of MOG induces specific T cells capable of causing neurological deficits resembling the manifestations of multiple sclerosis in humans. Nine days later, abdominal lymph nodes were removed to produce white blood cells (WBC). Cells were co-cultured in the presence of specific cytokines IL-2, IL-12 and IL-23 with MOG in a CO2 incubator at 37°C. Cytokines and MOG acted together as growth factors for T lymphocytes that only recognize MOG.
Example 2: Adoptive transfer of EAE

Expanded cells from the previous step were divided into two groups: 1. cells without separation ("as is" cells) and 2. cells after separation of harmful T cells. Separation of these cells was performed in the following manner.

a. Incubation with target protein conjugated to fluorophore PE.

b. Add to cytomagnetic beads that recognize the fluorophore PE. This step resulted in PE-protein-T cell-magnetic bead complexes.

The complex from b. was then passed through a column where only PE-protein-T cell-magnetic beads bound. This procedure was repeated twice.

Group 1 cells were injected into 3 mice (control group) and Group 2 cells were injected into 3 mice (treatment group). Harmful cells were isolated and removed from the second group.
Example 3: Evaluation of T cell numbers in lymph nodes after in vitro incubation

There are many different types of white blood cells in lymph nodes, including B cells and macrophages. Cell recognition was performed using a flow cytometry analyzer. A unique marker for T lymphocytes only, Thy1.2, was used to estimate the percentage of T lymphocytes in the extract. Figure 26 shows the results using single staining with Thy1.2. Positive staining for Thy1.2 (LF4-H) is displayed in the lower right quadrant of the graph. Therefore, 26.88% of the cells in the extract were found to be T lymphocytes. Non-T lymphocytes appeared in the left lower abdomen (72.99%). This staining was done before adding the PE protein, so the left and right upper abdomen is irrelevant. Cells examined were leukocytes within lymph nodes prior to initial separation by column.
Example 4: Assessment of MOG-activated T-cell numbers prior to isolation

Cells were then double-stained with the same T lymphocyte marker (Thy1.2-APC) as in Figure 26 and a second marker (Protein-PE) that binds to a protein already bound to PE. Double-stained cells appeared in the upper right flank of FIG. Cells examined were leukocytes within lymph nodes prior to initial separation by column. As seen in Figure 2, double staining of 5.15% of the cells, T lymphocytes binding protein, was performed. Staining in the upper left abdomen (12.08%) is positive staining for protein only.
Example 5: Evaluation of MOG-activated T-cell numbers after two rounds of isolation

Cell populations were then analyzed in-column using MOG-PE conjugates to isolate specific T cells. To monitor the efficiency of separation, the protein complex was passed through the column twice (Figure 28A: 1st time, Figure 28B: 2nd time). In each of these two tests, a new column was used and the fraction of cells passing through the column (ie, the fraction not bound to the column) was analyzed. Double-stained cells retained by magnetic beads in the column were subjected to flow cytometry analysis and the results are shown in Figures 28A and 28B.
Example 6: Evaluation of number of MOG-activated T cells in column (2 separations)

The cell population bound to the column was also analyzed following the same procedure for isolation of specific T cells. The conjugate was passed through the column twice (FIG. 29A: 1st time, FIG. 29B: 2nd time) as described above. Figures 29A and 29B show results for cells in the first column (Figure 29A) and cells in the second column (Figure 29B).
Example 7: Preclinical Results

Nine days after injection of cells into healthy mice, scores for both groups were as follows.

Control group 1: 3 mice received clinical scores of 1, 1, and 1.5 (see Table 1 below for score details). The mean clinical score was 1.2.

Treatment Group 2: Following depletion of noxious T cells, mice receiving cells had clinical scores of 0, 0, and 0 (see Table 1 below for score details). Mean clinical score was 0.

実施例8：多発性硬化症患者を対象とした観察臨床試験 Important note: Induction of EAE with MOG followed by transfer of cells to healthy mice was previously known to result in mild rather than full-blown disease. This is why higher scores were not observed for control group 1 disease.
Table 1: Evaluation of Clinical Signs of Experimental Autoimmune Encephalomyelitis (EAE)

Example 8: Observational clinical trial in patients with multiple sclerosis

The purpose of this study was to characterize and quantify a special subpopulation of white blood cells (leukocytes in multiple sclerosis patients) compared to subjects without multiple sclerosis and other autoimmune diseases. .

The primary objective of this study was to establish a pilot database of multiple sclerosis patients to determine their HLA types and their unique multiple sclerosis-associated peptide repertoires. This dataset enables the design of unique biological probes capable of recognizing and capturing specific leukocytes from blood-sampling patients and quantifying the specific multiple sclerosis-associated leukocytes from each patient Accumulated to make

Blood collection: A total of 60 confirmed eligible patients (10 without multiple sclerosis and other autoimmune diseases, 20 newly diagnosed, and 30 with known multiple sclerosis) ) were encouraged to participate in this study. All three groups had at least one visit, and at the time of blood collection, blood samples were taken to the histotyping laboratory for HLA typing and cell storage for in vitro assays according to ethics committee-described and approved protocols. delivered. The results of HLA genotyping were recorded and the abundance of each HLA genotype was calculated.

PBMC Purification: After arrival at the laboratory of the blood sample, the sample was used for separation and purification of PBMC or as whole blood for filtration procedures. A peripheral blood mononuclear cell (PBMC) is any peripheral blood cell with a round nucleus. These cells consist of lymphocytes (T cells, B cells, NK cells) and monocytes, red blood cells and platelets without a nucleus, and granulocytes (neutrophils, basophils, eosinophils) with multilobed have a nucleus In humans, lymphocytes make up the majority of the PBMC population, followed by monocytes and a small percentage of dendritic cells. PBMCs were extracted and purified using UNISEP tubes (Novamed, Israel) standard protocol and stored at −80 °C in serum-free freezing medium (Biological Industry, Israel) for future analysis.
Overview of Examples 9-12

Examples 9-12 describe the construction, expression, purification, and characterization of proteins involved in pathogenic T cell recognition, capture, and elimination.
Example 9: In silico construction of proteins

A sequence alignment of MHC class II molecules from human, rat, and mouse species provided the starting point for the protein studies described herein. As previously described (Burrows et. al., Protein Eng., 1999, 12(9):771-778; Chang et. al., J. Biol. Chem., 2001, 276(26):24170-24176), Expression vectors for human, rat and mouse pathogenic cell elimination proteins were designed.

Each protein was specifically designed according to the prospective experimental animal model and its genetic background (strain). For the human recombinant protein (BI2.002), the HLA class II: DRB*1501β1 subunit was used fused to the DRA*0101α1 subunit because it is the most common allele in multiple sclerosis patients. Sequences homologous to the human DR1501:0101 sequence for mouse (BI4.001) and rat (BI3.002) were used: C57 BL6 MHC class II I-Ab β1α1 subunit and MHC class II RT11 β1α1 (corresponding).

A 30 amino acid huMBP-(85-99)-peptide, followed by a linker sequence, cartridge was inserted into the β1α1 coding sequence between Arg-5 and Pro-6 of the β1 chain. Finally, we added nine nucleotides encoding three amino acids, two glycines and a cysteine at the C-termini of all three proteins.

The gene encoding the BIX.XX-GGC protein was synthetically cloned into the NcoI/XhoI restriction sites of the pET21d(+) expression vector by Genescript (USA) and transformed into a BL21(DE3) competent expression host (BioLab). did.
Example 10: Expression and in vitro folding

The pET21d+/BI X.XX-GGC vector was transformed into E. coli BL21 (DE3) competent cells (BioLab, Israel) for protein expression. Recombinant protein production was induced by the addition of isopropyl bD-thiogalactoside (IPTG) (BioLab, Israel) and collected by centrifugation.

Proper folding of pathogenic cell clearance proteins required disulfide bond formation. Proteins that require disulfide bonds for proper folding tend to form aggregates, also known as inclusion bodies. The reducing environment of the cytosol, which tends to destabilize disulfide bonds, leads to the formation of bacterial cytosolic protein aggregates. To extract pathogenic cell-removing proteins, cell pellets were lysed using a microfluidizer and non-soluble inclusion bodies containing pathogenic cell-removing proteins were sedimented by centrifugation.

The pellet containing misfolded proteins was denatured, purified using a protein anion exchange chromatography (AIEX) column, and refolded in a slow multistep dialysis process. Final yields of purified protein were analyzed using circular dichroism from 15-30 mg/L bacterial cultures. Multi-angle light scattering (MALS) mass spectrometry coupled linearly to the AIEX column indicates that the HIS-tagged protein is monomeric in solution (data not shown).
Example 11: Coomassie staining

Gels were stained with InstantBlue Coomassie staining solution (Expedeon) and exposed with a ChemiDoc XRS+ camera (Bio-Rad).

Coomassie staining of SDS-PAGE under reducing conditions shows that the BI protein is at a level of 85-95% purity (Figure 30A +DTT). Under reducing conditions, all BI proteins run on SDS PAGE as monomers. However, in non-reducing condition gels, the fraction of monomeric pathogenic cell-clearing proteins is approximately 50%, with the remainder mostly dimeric (FIG. 30B-DTT). Since these dimers are formed by disulfide bonds of reduced cysteine residues (at the ends of the protein chains), these cysteine residues are essential for surface binding and thus the ability of these dimers to bind to surfaces. Lose.
Example 12: Circular Dichroism (CD) and Thermal Transition Measurements and Analysis

CD spectra of pathogenic cell-clearing proteins were recorded using a J-810 spectropolarimeter (Jasco) in 0.1 cm pathlength, quartz cuvettes (Hellma, Malheim, Germany). All measurements were made in PBS. Data are presented as molar ellipticity after baseline subtraction of PBS. Spectra presented were the average of 5 scans from 260-190 nm. Secondary structures were deduced using the online DICHROWEB software. For stability studies, CD signals at 220 nm were recorded at several temperature ranges between 4 and 90° C. for all pathogenic cell-clearing proteins to generate denaturation curves.

According to the literature, circular dichroism measurements show that the proteins exhibit the expected secondary structure for these proteins (Chang et. al., J. Biol. Chem., 2001, 276(26 ): 24170-24176, Fig. 30B). Most proteins contain a combination of β-sheets and α-helices. Denaturation curves showed that the melting temperature (Tm) of all proteins was higher than the experimental temperature (25°C or 37°C), indicating that all proteins were stable and their structures remained intact at these temperatures. rice field.
Overview of Examples 13-15

Examples 13-15 describe surface modification of silicon wafers with BI X.XXX-GGC proteins, surface characterization, and atomic force microscopy of modified silicon wafers.
Example 13: Surface Modification

As in Figure 31, silicon substrate wafers were coated with BI X.XXX-GGC proteins in a three-step reaction. First, the wafers were coated with 3-aminopropyltriethoxysilane (APTES) followed by 4-maleimidobutyric acid sulfo-N-succinimidyl ester (sGMBS) crosslinkers, and finally the proteins were coated with the pathogenic cell-removing protein C It was covalently attached to the aminosilane-functionalized gate nitride surface through a terminal cysteine thiol group. Finally, each protein-coated wafer was coated with a protein layer, a sucrose protective layer.
Example 14: Surface Characterization

Ellipsometry measurements were performed on a variable angle spectroscopic ellipsometer (VB-200 VASE, Woollam Co.) around the Brewster angle (75°) of silicon.

Ellipsometry measurements revealed that the GMBS layer thickness, which corresponds to the diameter of the monomer, was approximately 6-8 Å for the APTES layer thickness, and the final thickness of the protein-coated silicon slides (APTES+GMBS+protein) was measured using mouse BI X. ~25 A for the XX-GGC protein, ~40 A for the rat BI X.XX-GGC protein, and ~50 A for the human BI X.XX-GGC protein (data not shown).
Example 15: Atomic Force Microscopy (AFM)

Atomic force microscopy (AFM) measurements were performed using AFM cantilevers (Nano-Wizards 3, JPK Instruments, Berlin, Germany).

AFM analysis shows that rat BI X.XXX-GGC protein-coated silicon slides and human BI XX.XX-GGC protein-coated silicon slides are coated with a very dense and uniform layer, thus without aggregation. It showed full protein binding capacity to the filter (see illustrations in Figures 32A-32B). Mouse BI X.XXX-GGC protein-coated silicon slides showed low density in AFM measurements.
Overview of Examples 16-17

Examples 16 and 17 describe in vitro testing of a preclinical prototype for extracorporeal hemofiltration.
Example 16: PBMC and Whole Blood (WB) Filtration

Before assembly of each filtration unit, each filter wafer was washed with TDW and dried with N2(g) or O2(g) to remove the sucrose layer. After assembling the filtration device to the peristaltic pump, the tubing was washed with heparin-supplemented saline. Tubing containing 5 ml of either whole blood from the patient or PBMCs purified from 5 ml of blood was connected to a filtration device and a peristaltic pump was used to establish a closed circle in which blood/PBMC flowed at 1 ml/min. was circulated for 1 hour. After the filtration process reached the filter unit, PBMC and blood were collected for further analysis.
Example 17: Environmental Scanning Electron Microscopy (ESEM)

All scans were performed using an FEI Environmental Scanning Electron Microscope Quanta 200 (FEI, USA). To achieve better scan contrast, some of the samples were coated with a gold/gold-palladium coating prior to scanning using a Polaron SC7640 sputter coater 0 (Quorum Technologies Ltd.). Scans were performed on protein-coated silicon wafers after incubation/filtration with PBMC or whole blood samples.
Summary of Examples 18-23: Preclinical Extracorporeal Hemofiltration Using Multiple Sclerosis Rat/Mouse Model

Examples 18-23 demonstrate the filtration performance of biological filters with silicon wafers coated with pathogenic cell-clearing proteins when applied to rodent multiple sclerosis models (mice and rats).
Example 18: Preclinical prototype design and assembly

We constructed biological filters with flow chambers that enable extracorporeal blood filtration using silicon wafers coated with pathogenic cell-removing proteins and evaluated their filtration capabilities. First, an animal model was selected that could be connected to a filtration device. Mice and rats are the most common animal models used to study multiple sclerosis. However, due to blood volume limitations of the filtration device, a rat model was chosen using Lewis rats with a minimum weight of 160 g on the day of filtration. The minimal size of the animal allowed sufficient blood to be removed for filtration without causing lethal effects on the animal.

A preclinical prototype included two separate filtration units that simultaneously filtered two different sources (PBMC, whole blood or two animals). The prototype had three key parts, a baseplate and two filtration heads. Each head subunit included inlet and outlet ports with sockets to hold filters and luer lock connectors for fast and efficient assembly of medical tubing. The base and head were made from polyetherimide (ULTEM 1000) which has both biocompatibility and good strength properties. All prototype subunits were molded using a computer numerically controlled (CNC) milling machine, assembled and sealed prior to each filtration procedure. The filtration unit was connected to a Minipuls 3 (Gilson) peristaltic pump via Tygon® and Pharmed® tubing to allow efficient blood/body fluid flow to the subject.
Example 19: Animal Models, Experimental Autoimmune Encephalomyelitis (EAE), and Clinical Evaluation of EAE

C57BL/6JOlaHsd mice were supplied by Envigo (Israel) from Jackson Laboratory (Bar Harbor, Maine, USA). Mice were housed in an animal care facility in accordance with approved regulations for the use of animals in research. LEW/SsNHsd rats were supplied by ENVIGO from nuclear colonies obtained from the National Institutes of Health, Bethesda, Maryland, USA. Female rats aged 7-10 weeks were used. All animals were cared for and handled in accordance with the principles set forth in the Declaration of Helsinki for the Use of Animals in Research and National Ethics Committees.

Experimental autoimmune encephalomyelitis (EAE) is the most common animal model and often serves as a "proof-of-principle" model for the efficacy of novel therapeutic strategies. Induction of EAE is particularly useful for investigating neuroinflammatory pathways in multiple sclerosis disease as they share many clinical and pathophysiological features, including the adaptive immune system. Although the EAE model can be derived in many animals (eg, mice, rats, minipigs, guinea pigs, chickens, primates), the mouse model was used due to its ease of implementation and rapid and robust results. EAE utilizes the immune system's response to brain-specific antigens to induce inflammation and destruction of antigen-carrying structures (such as cells and myelin sheaths), resulting in multiple sclerosis similar to that observed in multiple sclerosis patients. produce similar pathological features.

An emulsion consisting of the antigen of choice and complete Freund's adjuvant (CFA) in mouse models (MOG35-55 peptide (Ray Biotech Inc., USA) in mouse models and g.pMBP68-82 (Genscript, USA) in rat models was injected subcutaneously. , pertussis toxin was injected intraperitoneally on the day of immunization and 2 days later.

Animals were observed daily after induction of encephalomyelitis. Clinical signs of EAE appeared 12-16 days after induction. Clinical disease scores were 0 - no paralysis, 0.5 - decreased tail tension, 1 - tail paralysis, 1.5 - hindlimb paresis, incoordination, 2.5 - hindlimb hemiplegia, 2.5 - bilateral hindlimb paralysis, weakness of both forelimbs. , 3 - bilateral hindlimb paralysis, forelimb hemiplegia, 3.5 - bilateral hindlimb paralysis, bilateral forelimb paralysis, 4 - quadriplegic animal in critical condition, 5 - death.

The safety and tolerability of hemofiltration were also evaluated. Ten EAE rats were filtered on different days (days 4, 6, 8, 4+8) and compared with 5 untreated EAE rats. No mortality was observed as a result of filtration up to 30 days after filtration. Weight loss was similar to the control group, and no changes in blood biochemistry and hematology parameters were observed after filtration.

Based on safety evaluation studies, a preliminary pilot clinical study was conducted using n = 34 rats divided into five groups shown in Table 2.
Table 2: Rat Groups in Preliminary Pilot Clinical Trials

No deaths were reported in all groups. Weight loss was similar in all groups and blood tests showed no difference (data not shown).

Disease activity was assessed from day 8 until spontaneous remission. No improvement in disease activity was seen in rats receiving sham filtration compared to untreated rats (Fig. 33A). Filtration on day 4 showed milder disease induction, with a lower peak on day 14 (1.5±0.28 vs. 2.06±0.2, respectively) (FIG. 33B). A single 1-hour filtration on day 6 showed the same onset and time to peak, but a significantly faster recovery was observed on day 16, 48 hours before the control group, and on days 16 and 17. The p-values for both eyes were p<0.01 (Fig. 33D). Animals filtered on day 5 showed similar results to the untreated group (FIG. 33C), showing a slight non-significant shift to the peak of disease progression.

実施例19：血液生化学的検査および血液学的検査 Interestingly, there is another way to analyze clinical score results. Since the onset of disease varies among rats (8-14 days), it is common to determine the date of onset separately for each animal and set this day as day 0 (Pollak et. al., Neuroimmunology 2003; Lange et. al. Ann Rheum Dis 2005; Ringheim GE et. al. Frontiers in Neurology, 4.2013, supra). All three groups were found to show a reduction in peak scores compared to untreated animals (Table 3 and Figures 34A-34D), with this procedure having a greater effect than observed in Figures 33A-33D. suggests that
Table 3: Comparative analysis by date of onset.

Example 19: Blood biochemistry and hematology

Rats were bled by retro-orbital sinus puncture and bled twice 4 days after EAE induction and 48 hours after filtration. Blood and serum were sent for analysis by the US Institute of Medicine (Israel) for a whole blood hematology and chemistry panel.
Example 20: Extracorporeal hemofiltration

LEW/SsNHsd rats were anesthetized with an isoflurane/O2 mixture using an isoflurane anesthesia machine during the entire filtration procedure. Two tail cannulae were made per animal using a 27G cannula, an arterial cannula for blood collection and a venous cannula for blood collection. Each rat was connected via an arterial cannulation to a filter inlet port to allow blood flow to the filter, which flowed through an outlet port to a peristaltic pump, which pumped 0.8-1 ml. Blood was returned to the subject's body via venous cannulation at a flow rate of /min.

The filtration unit and tubing set were prewashed with heparinized saline (0.9% sodium chloride injection supplemented with 25 units/ml of heparin) to prevent hypovolemic shock or blood clotting in the animal during the procedure. .
Example 21: EAE induction and PBMC enrichment in mice

Mouse models for multiple sclerosis were used as a more viable resource to establish a more robust and less complex method of obtaining cells for research and development needs. EAE was induced in C57/6 JOLAHsd female mice (described above) and spleens were removed for splenocyte isolation and activation. The induction of disease was peptide-specific, using mouse MOG35-55 as the encephalomyelitis-inducing peptide, and the same peptide was treated in the presence of IL-2, IL-12 and IL-23 for 72 hours to stimulate T helper cells. Used for in vitro enrichment and enrichment of specific clones.
Example 22: FACS

Flow cytometry acquisition was performed on a BD FACS-Can to II using standard protocols for staining approximately 1-2 x 106 cells per sample. At least 250,000 events were recorded for each sample and data analysis was performed using FCS express version 6.0 (De Novo software). All antibodies and tetramers used for FACS labeling are listed in Table 4 below.
Example 23: Fluorescence Microscopy

実施例24および25の概要 To visualize attachment of cells to the 2D filters, antibodies (Table 4) were applied onto the biological filters after filtration according to the manufacturer's recommendations for immunohistochemical staining. Surfaces were visualized using the Leica Confocal Imaging System SP5.
Table 4: List of antibodies and tetramers used for analysis.

Summary of Examples 24 and 25

Examples 24 and 25 describe observational clinical studies in human patients.

The immune system is conventionally divided into innate immunity and adaptive immunity. Innate immunity is nonspecific and provides the first line of defense against pathogens, whereas adaptive immunity is thought to be due to specific repetitiveness. Adaptive immunity is composed of both cellular and humoral components. B cells recognize specific targets in soluble form via antibodies, whereas T cells when presented on HLA molecules expressed by nucleated cells (type I) or antigen-presenting cells (type II) only recognize targets.

In autoimmune diseases, the immune system identifies self-antigens as foreign and attacks the body in a wide range of diseases, from organ-specific (eg, thyroid or pancreas) to systemic (eg, systemic lupus erythematosus). Current treatments for autoimmune diseases focus on general and general immunosuppression, which is associated with significant side effects and makes individuals more susceptible to infections.

Thus, in the context of multiple sclerosis (MS), some embodiments described herein are directed to specific T cells that recognize myelin-associated proteins and are involved in disease initiation and progression in multiple sclerosis. The purpose is to remove cells. The biological filter embodiments described herein are capable of recognizing, trapping, and removing these target cells from the peripheral blood of multiple sclerosis patients.

The first challenge was the expression and purification of the capture protein. HLAII-type recombinant proteins homologous to human DR were designed and expressed as described in the Examples below. Based on the physiological interactions between T cells and antigen-presenting cells (APCs), these peptide-loaded proteins are able to recognize and bind to the corresponding T cell receptors of related clones. .

The next challenge was the immobilization of proteins to biocompatible surfaces. As described above, we successfully coated a uniform monolayer with the target protein. All optical and biochemical validations were positive including ellipsometry for layer thickness measurements.

To demonstrate real-time live filtration of cell suspensions, we designed a prototype device embedding a 2D filter connected to a peristaltic pump that circulates the sample. This prototype device was used in both preclinical experiments and ex-vivo human blood validation of the hemofiltration platform technology described herein. In the preclinical studies described, this method was shown to be safe and well tolerated in both naïve and EAE-induced rats. Proof-of-concept experiments in rats also confirmed the following findings:

1. Rats must be anesthetized for at least 1.5 hours to perform filtration. It should be emphasized that a longer duration of anesthesia is an important risk factor for survival and thus this time should not be extended further in order to achieve more efficient elimination of the associated T cells.

2. The device prototype is a preliminary prototype and is subject to flow restrictions and exposure to air, both of which may affect filtration quality.

3. From accumulated data, it was observed that whole blood filtration was less effective than filtration of PBMCs where only PBMCs were in contact with the filter. Experiments performed on human PBMC from multiple sclerosis patients were much more effective, even within 1 hour after filtration (Figures 35A-35F, Figure 36). In Figures 11A-11F, primary lymphocytes were gated according to forward and side scatter. FITC-labeled CD19 cells (representing B cells) were then excluded against APC-labeled CD4+ cells (representing helper T cells) and finally PE-positive (clone-specific T helper cells within the total helper T cell subpopulation). cell) was calculated. Shown here is a comparison of pre-filtration PBMCs (FIGS. 35A-35C) and post-filtration PBMCs (FIGS. 35D-35F) in the same patient.

Therefore, whole blood filtration in rats appears to be less efficient for filtration.

4. Filtration on day 4 after disease induction showed superiority compared to days 5 or 6, whereas on days 5 and 6 most T cells were removed from the circulation to the central It migrates to the nervous system and induces disease. On day 4 of filtration, the filters were able to remove a significant proportion of EAE-associated T cells from the circulation causing moderate effects.

Examples 24 and 25 validated the ex vivo approach, in which the prototype device produced over 40% specificity by filtering PBMC from six different multiple sclerosis patients within 1 hour of filtration. demonstrated the ability to eliminate T cell clones. This was verified by cytometric analysis as described.

Both ex vivo and in vivo experiments suggest that a more appropriate approach in humans begins with the generation of PBMC fractions, followed by specific multiple sclerosis-associated T cell depletion and filtering using biological filters. It is suggested to include a leukapheresis procedure to maintain the integrity of the patient's immune system, thus relocating such PBMCs to the patient.
Example 24: HLA Genotyping of Multiple Sclerosis Patients

Up to this point, a total of 26 subjects have been enrolled in the observational clinical trial described in the methods. Of these, 8 subjects were newly diagnosed with multiple sclerosis (group A), 16 subjects were diagnosed with multiple sclerosis for more than 3 years (group B), and control subjects had no history of autoimmunity. There were 2 patients (group C). The primary objectives of this cohort were to obtain data on HLA type I and II haplotypes across study arms and to establish a small reservoir biobank of frozen PBMC samples from these subjects. Cells were thawed when necessary for assessment of specific binding to biological filters. A key interim summary of allele frequencies of different HLAI types (A, B and C) and type II (DR and DQ) is shown in Tables 5 and 6 below. For example, DRb15:01 has been found to be present in 30–50% of patients with multiple sclerosis in the United States (Hollenbach et al. J Autoimmun., 2015, 64:13-25), and Israeli Jews is also found in 17-24% of patients (Kwon et al., Arch Neurol., 1999, 56(5):555-560), with a higher prevalence than the general (non-MS subjects) population. The result was shown.

表6：多発性硬化症患者におけるHLA II型対立遺伝子頻度(N = 24)

実施例25：多発性硬化症患者の血液濾過の検証 So far, 25% of multiple sclerosis subjects in this cohort carry the 'notorious' allele (12.5% allele frequency), and harvested PBMCs were used to assess filter performance. The foregoing are merely examples. Other target proteins can be determined by combining collected data with known data available in the literature for target gene clusters in multiple sclerosis patients.
Table 5: HLA Type I Allele Frequencies in Multiple Sclerosis Patients (N = 24)

Table 6: HLA Type II Allele Frequencies in Multiple Sclerosis Patients (N = 24)

Example 25: Validation of Hemofiltration in Multiple Sclerosis Patients

To date, 26 subjects have been enrolled in an observational clinical trial. Of these, 6 subjects expressed the target allele DRb15:01. Blood was drawn from these subjects to perform ex vivo validation of the hemofiltration techniques described herein. Upon arrival of heparinized blood from the hospital, a portion of blood was taken for PBMC isolation and the remainder was used as is. At the same time, both the sample, whole blood (WB) and PBMC-purified fraction, were circulated through the prototype chamber for 1 hour at a constant flow rate of 1 ml/min using a peristaltic pump. Samples were taken before and after filtration for analysis using flow cytometry.

A commercially available tetramer capable of specifically binding only to T cells expressing the T cell receptor for human MBP85-99, presented on HLA type II, DRb15:01 (Table 4). ) was used. This made it possible to detect specific target T cells to be depleted. A decrease in the percentage of specific cells in total CD4+ T cells indicates recognition, capture and removal of those cells by the prototype filter during the procedure. FACS analysis showed a mean 42% (range 21%-65%) target cell removal after 1 hour filtration of the isolated PBMC fraction (T test for corresponding samples at p<0.01). was, Figures 35A-35F). In addition, at the same time, no significant changes were observed in either total B-cell subpopulations or total helper T-cell subpopulations resulting from filtration of PBMCs.

In vitro filtration of whole blood suffers from technical limitations of the filtration procedure, exposure of the blood to air, non-specific binding of blood components to the device (except for the filter surface itself), and to the post-filtration whole blood sample. gave non-specific results due to the limitations of FACS analysis.

Two cases (204, 211, see Figure 36) showed the highest pre-filtration levels of clone-specific CD4+ T cells. Interestingly, these subjects were under treatment with Tysabri. Tysabri binds to integrin α4 and blocks migration of lymphocytes from the peripheral blood to the central nervous system by blocking integrin α4. These circumstances suggest that combination therapy with Tysabri may induce filtration potency and efficacy.

After filtration with whole blood or PBMC, human BIX.XX-GGC protein-coated silicon slides were washed with water, coated with gold and analyzed by ESEM. Results showed binding of cells to filters that were 6-9 nm in diameter, and some larger cells that were 12 nm in diameter (FIGS. 37A and 37B). Figure 37A is an SEM photograph of human BIX.XX-GGC protein-coated silicon slides after filtration with subject whole blood. Figure 37A is an SEM photograph of human BIX.XX-GGC protein-coated silicon slides after filtration with subject PBMCs.

In another experiment, after filtration, the filters were washed with RPMI and antibodies against CD4 (T cell marker), CD19 (B cell marker), and tetramers to stain specific T cells that recognize the HLA complex. stained with Results showed binding of T cells to the filters and specific T cells were identified as well (data not shown). 2-4×10 ⁶ cells extracted from EAE mouse splenocytes were diluted in RPMI medium (Biological industries, Israel) and filtered onto mouse BIX.XX-GGC protein-coated silicon slides for 1.5 hours. Slides were washed with PBS and water, dried and coated with gold for ESEM measurements. ESEM showed binding of cells 6-8 microns in diameter to the filter. Incubation of cells extracted from splenocytes from healthy mice showed little binding to the filter compared to cells from EAE-induced mice, demonstrating the specificity of the filter (see images in Figures 37A and 37B). .

For confocal microscopy, slides were washed with PBS after incubation with cells and then stained with a commercially available stained tetramer to stain specific T cells that recognize MHC II complexes. (Figures 38A-38C). FIG. 38A is an ESEM photograph of BIX.XX-GGC protein-coated silicon slides after filtering cells extracted from EAE mouse splenocytes. FIG. 38B is an ESEM photograph of BIX.XX-GGC protein-coated silicon slides after filtration of cells extracted from splenocytes of healthy mice. FIG. 38C is a confocal micrograph of tetramer staining of BIX.XX-GGC protein-coated silicon slides after filtration of cells extracted from EAE mouse splenocytes.
Example 26: Preparation of polysulfone/polyelectrolyte-based polymer matrices for entrapping biomolecules and biological substances

In this example, a matrix comprising a combination of high-performance thermoplastic polymers (e.g., polysulfones and derivatives) and polyelectrolytes (e.g., polyacrylic acid and poly(2-aminoethyl)acrylamide) was formed with polyacrylic acid (PAA ) (5-40%) and polysulfone (PSf) (60-95%). The matrix can be a thin film, filament, hollow fiber, or any other polymeric structure accessible to aqueous solutions. Can the carboxyl groups of PAA interact directly with other chemical or biological molecules or other functional groups (e.g., amine or maleimide groups) that interact with macromolecules after they are made by solidifying a solid surface? , or can be transformed to generate/design the final surface to capture specific elements (eg, proteins, cells or other components).

Preparation of polysulfone-poly(2-aminoethyl)acrylamide membranes (films or fibers): The dry/wet static technique is the preparation technique used to fabricate hollow fiber membranes, a schematic of which is shown in Figure 39. show. In this figure, the membrane film/fiber consists of a polymer combination of polysulfone and polyacrylic acid, which is modified during manufacture to poly(2-aminoethyl)acrylamide, and which, in a specific manner, interacts with the protein of interest. It is activated with a covalently attached maleimide linker. First, a casting solution was prepared as follows: 8% additive (PAA) was dissolved in dry DMF (dimethylformamide) at 100°C, the solution was stirred with a magnetic stirrer at 500 rpm for 2 hours, A homogeneous solution was obtained. In parallel, 16% solid PS was dissolved in dry pure DMF solvent. After obtaining a homogeneous mixture, PS was added dropwise to the PAA solution. The mixed material was stirred at 100° C. and 700 rpm until a miscible mixture was formed. The entire solution was then introduced into a sonication bath maintained at 40°C until the mixture became a miscible mixture. The percentage of mixture composition used to prepare the mixture solution varied depending on the strength requirements of the final product. 5-40% by weight of polyacrylic acid (PAA) was mixed with polysulfone (PSf). The PSf-PAA mixture was forced through a syringe on a wetted glass sheet or into a water bath while pulling parallel with forceps to create fibers. The glass sheets can be wetted with Milli-Q water (18.3 MΩ·cm) at 18° C. or with a physiological solution. Using this method, 0.2-0.3 μm wide fibers were made as hollow fibers. The thickness of the intermediate pore was determined by the proportion of PAA in the PSf-PAA mixture. For 25% PAA the pore diameter was ~200 microns and for 33% PAA the diameter was ~100 microns (Figures 41A-41C). Fibers composed of 25% PAA (Figures 41A and 41B) or 33% PAA (Figure 41C) produce hollow fiber structures 200-300 microns wide.

A film of PSf-PAA was also prepared by dropping the blended solution onto a glass sheet in a coagulation bath containing a sufficient amount (completely covering the slide) of Milli-Q water (18.3 MΩ cm) at a temperature of 18 °C. From this mixture very thin films were also supported on glass or silicon base sheets with aminopropyltriethoxysilane as an adhesive layer. It can be made using a spin coater (0.5-3% w/v final concentration of both components in DMF solution). The membranes/fibers are washed with water and stored until use. The PSf-PAA membranes/fibers are then reacted with ethylenediamine to generate functional amine groups in place of the carboxyl groups of PAA to produce PSf-poly(2-aminoethyl)acrylamide fibers/films. Different protocols for making fibers and hollow fibers are available in the literature (eg Choi et al, European Polymer Journal, 2010, 46(8):1713-1725). The procedure employed here was adopted due to its ease of use and the fact that it does not require special facilities or special equipment.

Maleimide activation with linker elongation: Sulfo-N-succinimidyl 4-maleimidobutyrate (sGMBS) was utilized as the maleimide linker. sGMBS is an active ester-terminated carbohydrate that interacts with anim nucleophiles on polysulfone-poly(2-aminoethyl)acrylamide membranes. sGMBS sodium salt was dissolved in PBS (pH = 7.2) to a concentration of 1 mM immediately before use and incubated with polysulfone-poly(2-aminoethyl)acrylamide membranes at 25°C for 18-22 hours.

Protein-maleimide interaction: proteins of interest (e.g. HLA-derived proteins) have reduced cysteine residues at the protein terminus (e.g. C-terminus) in certain organisms (e.g. bacteria, yeast, insect or mammalian cells) Produced as a recombinant protein. 10 μM of pure protein diluted in PBS (pH = 7.2) was incubated with polysulfone-poly(2-aminoethyl)acrylamide membranes activated with maleimide functional groups for 2 hours at 25°C, resulting in a protein monolayer on the surface. (Figs. 41A, 41B, 42A, 42B, 43), about 40-50 Angstroms thick (measured by AFM on silicon slides and ellipsometer), with stable thioether bonds between protein and matrix. FIG. 18A shows the AFM topography of a monolayer of dense proteins. Figure 18B is an AFM profile graph recorded from a protein-coated silicon slide showing a layer thickness of 4.5 nm. The graph in Figure 19 shows three samples: PSf inactivated, PSf activated sheet with protein 1, and PSf activated sheet with protein 2 (two mutants of the human GGC protein). Both protein-activated PSf sheets show a peak at approximately 163.5 eV, corresponding to disulfide bonds (S-S) that appear only in structured functional proteins.

Protein Coated Membrane Activity: These covalently modified protein membranes can be used for several applications in the biological/biochemical/medical fields. This can be used in analytical tests to quantify and characterize protein partners/targets (eg, other proteins, cells, or other biological or non-biological molecules). Based on protein interactions with partners, specific pharmaceutical applications can be applied, e.g., apheresis or dialysis special filters, which depend on the interaction of specific cells with protein-coated membranes, and the patient's bloodstream or blood Those cells can be removed from the fraction (PBMCs, etc.).

The foregoing description, including examples, has been presented for purposes of illustration. It is not exhaustive and is not intended to be limited to the precise forms or embodiments disclosed. Modifications and adaptations of the embodiments will become apparent from consideration of the specification and embodiments of the disclosed embodiments. For example, although certain components are described as being coupled together, such components may be integrated together or distributed in any suitable manner.

Further, although exemplary embodiments are described herein, the scope does not cover equivalent elements, modifications, omissions, combinations (e.g., aspects across various embodiments), adaptations based on the disclosure. and/or modifications. Claim elements should be construed broadly based on the language used in the claims, as set forth in the examples set forth herein or in the prosecution of the application. The examples are not intended to be limiting, and these examples are to be construed as non-exclusive. Further, the steps of the disclosed methods can be modified in any way, including rearranging steps and/or inserting or deleting steps.

The features and advantages of the present disclosure will be apparent from the detailed specification, and thus the appended claims are intended to cover all systems and methods that fall within the true spirit and scope of the disclosure. . As used herein, "one or more" is meant when no number is specified. Similarly, the use of the plural does not necessarily imply the plural unless it is clear in the given context. Terms like "and" or "or" mean "and/or" unless stated otherwise. In addition, since numerous modifications and variations will readily occur from reviewing this disclosure, it is not desired to limit the disclosure to the precise construction and operation shown and described, and all suitable modifications and equivalents are therefore not desired. are within the scope of the present disclosure and can be used.

The disclosed embodiments, whether implemented in connection with a filter, apparatus, system, computer-readable medium or method, include any of the features set forth in the following bullet points alone or May include in combination with one or more of the other bulleted features:
● Inactive surface medium ● Human leukocyte antigen (HLA) proteins placed on inert surface medium ● Antigen peptides bound to HLA proteins on inert surface medium ● Antigen-specific T when T cells contact the complex Selected antigenic peptides and HLA proteins that allow cell receptors to bind antigenic peptide and HLA protein complexes and anchor specific T cells through the complexes to an inert surface medium Sheet material, Inert surface media including mesh structures, fibers, gels, liquids, or beads Non-reactive media including polysulfone or polysulfone derivatives, glass matrix, silicon matrix, polydimethylsiloxane (PDMS), polycarbonate, polyetherimide (Ultem), or tritan Active surface media • Inert surface media including polysulfones • Inert surface media including polyelectrolytes • HLA proteins placed on inert surface media via covalent, non-covalent interactions or adsorption • Maleimide analogues HLA proteins placed on an inert surface via an inert surface medium containing polyethylene glycol (PEG) or PEG derivatives, polystyrene, avidin and/or streptavidin An anchor position of the HLA protein is at least in the HLA binding groove HLA proteins arranged on an inert surface medium so that they are spaced from each other by a width HLA proteins comprising one or more monomers or multimers Cleaved HLA proteins containing a cysteine as the C-terminal residue Engineered HLA proteins • C-terminal cysteines linked to HLA proteins via peptide linkers • HLA proteins HLA typed to match patients • Capable of selectively binding to antigen-specific T cell receptors antigenic peptides that are synthetically engineered and loaded onto HLA proteins to form HLA-peptide complexes that can be formed; recombinantly produced HLA proteins; antigenic peptides derived from proteins associated with multiple sclerosis; Antigenic peptides include myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), myelin proteolipid protein (PLP), opaline protein, oligodendrocyte-specific protein (OSP), myelin-associated glycoprotein (MAG ), or a combination thereof The antigenic peptide is MBP _87-99 , MBP _85-99 , MBP _83-96 , MBP _217-231, MBP _88-102, MBP _282-296, PLP _91-110, PLP _131-151, PLP _283-252, PLP _263-277, PLP _58-72, PLP _13-27, OPALIN _46-60, OPALIN _27-41, OPALIN _127-141, MOG _210-224, MOG _29-43, MOG _176-190, MOG _225-239, OSP _74-88 , OSP _114-128, MAG _8-22, MAG _467-481, MAG _529-543 , or a combination thereof Filters comprising multiple layers configured to allow fluid flow between the filters Selectively bind to antigen-specific T-cell receptors a filter medium for hosting substances that bind human leukocyte antigen (HLA)-myelin-peptide complexes, selected to bind to myelin-specific T-cell receptors, thereby binding HLA-myelin peptide complexes; Filter host materials that allow specific binding of the recognizing T cell population ● HLA-myelin-peptide complexes each containing an antigenic peptide and an HLA protein ● Filter media containing an inert surface ● Filter media containing beads ● Sheet material filter media containing fluids filter media containing polysulfone or polysulfone derivatives, glass matrix, silicon matrix, polydimethylsiloxane (PDMS), polycarbonate, polyetherimide (Ultem), or tritan containing polyelectrolytes Filter media HLA-myelin-peptide complexes disposed on the filter media via covalent bonds, non-covalent interactions or adsorption HLA-myelin-peptide complexes disposed on the media via maleimide analogues • HLA-myelin-peptide complexes positioned on the medium via maleimide analogues • Anchor positions for the complexes positioned on the filter medium such that they are spaced from each other by at least the width of the HLA binding groove HLA-myelin-peptide complexes Use of HLA proteins that are either HLA I and/or HLA II Host materials containing complexes of HLA proteins and antigenic peptides derived from non-myelinous multiple sclerosis-associated proteins white blood cells from other fractions of whole blood A first stage area configured to hold a blood separation device that can be separated A blood fraction outlet configured to allow return of an inlet, a leukocyte outlet, and other fractions into the patient's body a blood separation device having a first pump for conveying blood from a patient through a first stage region a second stage configured to hold a biological filter containing human leukocyte antigen (HLA)-peptide complexes Region - Having one or more inlets and one or more outlets, the first and second stage regions permit flow from the leukocyte outlet of the blood separation device to one or more inlets of the biological filter a second pump for recirculating leukocytes from one or more outlets of the biological filter to one or more inlets of the biological filter a first stage region and Multiple electrically controllable valves for directing blood through the second stage area Control the first pump to allow blood to flow through the first stage area until a certain amount of white blood cells are separated and transported to the second stage area one or more processors set to flow through the staging area disabling the first pump when a certain amount of white blood cells are separated and transported to the second staging area enabling the second pump and Multiple valves are controlled to recirculate a certain amount of white blood cells through a biological filter for a period of time sufficient to separate pathogenic T cells from non-pathogenic white blood cells Return of non-pathogenic white blood cells to the patient - A plurality of electrically controllable valves, controllable by one or more processors, recirculate white blood cells while a second pump is activated to recirculate a certain amount of white blood cells through a second stage biological filter. one or more electronically controllable valves controllable by one or more processors activates a second pump and a second stage biological filter One or more processors control multiple electrically controllable valves to prevent leukocytes from moving from the first stage area to the second stage area while recirculating a certain amount of leukocytes through the to process the leukocytes in batches in the second stage area, recirculate the first batch of leukocytes in the second stage area, and then one or more processors process the second batch of leukocytes into the second stage biology. A blood separation device configured to separate blood using apheresis A blood separation device configured to separate blood using centrifugation Constructed blood separator Filtration A blood separation device configured to separate blood using a membrane A blood separation device configured to mechanically bind leukocytes to a cell-specific matrix Allows binding of leukocytes to cell-specific antibodies the one or more processors configured to control a blood mixing device that mixes whole blood and/or a fraction of non-pathogenic white blood cells prior to return to the patient's body A blood mixing device, which consists of: A biological filter consisting of multiple layers, each layer having a human leukocyte antigen (HLA)-peptide complex thereon About three of the blood fractions from which the biological filter was collected A second stage area sized to contain ~50ml At least one of said first and second pumps is a peristaltic pump Stores blood from said patient prior to separation in a blood separation device an arterial pressure control unit one or more processors configured to control one or more valves to add red blood cells and saline prior to returning other fractions of whole blood to the patient one or more processors configured to control one or more valves to supply anticoagulant to the staging area a biological filter configured to selectively bind pathogenic T cells A tubing set for removing pathogenic T cells from a patient's blood A blood separator used to separate white blood cells from other fractions of whole blood, with an inlet, a white blood cell outlet, and a blood fraction outlet A tubing set containing a first stage region with a human leukocyte antigen (HLA)-peptide complex containing one or more primary inlets, one or more primary outlets, one or more recirculation inlets, and one or more a tubing set having a second stage region containing a biological filter with a recirculation outlet of a tubing set having a recirculation loop interconnecting one or more recirculation outlets with a recirculation inlet patient to first stage One or more blood suction tubes to carry blood to one or more inlets of the region One or more intermediate tubes to carry blood from the leukocyte outlet of the first stage region to the primary inlet of the second stage region Within the patient One or more first stage bypass tubes for carrying the blood fraction from the blood fraction outlet of the first stage area for return to the patient One or more first stage bypass tubes for carrying the white blood cells from the primary outlet of the second stage area for return to the patient One or more leukocyte return tubes A primary inlet of the second stage area that is common with the recirculation inlet of the second stage area A primary outlet of the second stage area that is common with the recirculation outlet of the second stage area Common one or more processors configured to receive first data related to treatment of a plurality of patients sharing a common peptide that causes activation of HLA and disease-associated T cells of the disease, further progression of the disease; Given that a greater number of different peptides activate disease-associated T cells than at earlier time points, the first data include the progression of common peptides that activate T cells over time. One or more processors One or more processors that may be configured to receive second data associated with a particular patient having common HLA and common peptides, wherein the patient has a disease in which the first set of peptides at a stage of disease that activates a first subpopulation of relevant T cells and a second set of peptides does not activate a second subpopulation of disease-related T cells a second set of peptides in a particular patient one or more processors configured to determine, using the first data, that the second set of peptides activates a second subpopulation of disease-associated T cells one or more processors configured to assist in taking remedial action to remove a second population of disease-associated T cells from a particular patient prior to the removal of disease-associated T cells from a particular patient; Outputs instructions to remove a second subpopulation Outputs information for use in building filters containing a second set of peptides predicted to cause future adverse conditions HLA typing and related peptides stripping of peptides from HLA complexes and determination of peptide sequences HLA typing based on blood analysis and information about said peptides based on analysis of tissue-specific and disease-related biological fluids cerebrospinal Analysis of liquid peptide data Comparison of disease-related parameters such as years from onset, symptoms, treatment, HLA typing analysis, and analysis of peptides presented by corresponding HLA proteins A first peptide that is a variant of the same peptide a set and a second peptide set; a first peptide set and a second peptide set that are different from each other; one or more processors configured to identify an additional set of consensus peptides that do not activate disease-associated T cells; Determining that additional sets of peptides correspond to further disease progression Determination of disease-related T cells from the patient before additional peptide sets activate additional subpopulations of disease-related T cells Output of commands to remove additional subpopulations of disease-associated T cells Output of data for use in building filters containing additional peptide sets Additional peptides identified one or more processors configured to adjust treatment of the patient based on the set adjusting treatment of the patient based on the identified second set of peptides the first subpopulation of disease-related T cells and the disease-related Simultaneous depletion of a second subpopulation of T cells Simultaneous depletion of the first subpopulation of disease-related T cells, a second subpopulation of disease-related T cells, and an additional subpopulation of disease-related T cells Myelin-derived treatment of multiple sclerosis with a focus on non-myelinic central nervous system proteins including peptides or aquaporin channels Myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), myelin proteolipid protein (PLP) , opaline proteins, oligodendrocyte-specific proteins (OSPs), myelin-associated glycoproteins (MAGs), or combinations thereof MBP _87-99 , MBP _85-99 , MBP _83-96 , MBP _217-231, MBP _88-102, MBP _282-296, PLP _91-110, PLP _131-151, PLP _283-252, PLP _263-277, PLP _58-72, PLP _13-27, OPALIN _{46-60 ,} OPALIN _27-41, OPALIN _127-141, MOG _210-224, MOG _29-43, MOG _176-190, MOG _225-239, OSP _74-88 , OSP _114-128, MAG _8-22, MAG _{467-481 ,} MAG _529-543 , or a combination thereof; Collection of biological fluids containing specific cells from patients; Extracorporeal flow of biological fluids through a binding medium-host material Returning biological fluids, excluding specific trapped cells, to the patient's body Biologically filtering whole blood or at least one of the blood fractions Cerebrospinal Biological filtration of fluids Biological filtration of bone marrow Biological filtration of synovial fluid Biological filtration of fluid from alveolar lavage Biological filtration of ascites Polyethylene glycol (PEG) or PEG derivatives , polystyrene, avidin and/or an inert surface containing streptavidin Biological filtration media containing one or more of polysulfone or polysulfone derivatives, glass matrix, silicon matrix, polydimethylsiloxane (PDMS), polycarbonate, polyetherimide (Ultem), or tritan ● Biological filtration media comprising polysulfone ● Biological filtration media comprising polyelectrolytes ● Biological filtration media comprising one or more of sheet materials, liquids, mesh structures, fibers, gels, or beads ● Humans A biological filtration medium comprising leukocyte antigen (HLA)-peptide complexes, each said HLA-peptide complex comprising HLA proteins and peptides comprising HLA I and/or HLA II, or truncated forms thereof A biological filtration medium containing HLA proteins A biological filtration medium containing HLA designed to contain a cysteine residue at the C-terminus A HLA-peptide complex positioned on the medium via a maleimide analog Biological filtration media containing antibodies Biological filtration media containing antibodies Biological fluids are circulated through the biological filtration media and returned to the patient using peristaltic pumps Biological filtration media contain fluids Organisms Biologically filtered specific T cells contain one or more CD4+ cells or CD8+ cells T cell receptors specific for antigenic peptides derived from proteins associated with autoimmune diseases, trapping T cells A biological filter configured to treat multiple sclerosis A biological filter configured to trap pathogenic cells associated with cancerous diseases, including hematologic or solid tumors identification of the patient's human leukocyte antigen (HLA) type as part of the construction of the biological filter identification of one or more immunogenic peptides associated with the patient's disease Recombinant, synthetic, or endogenously produced/made HLA-peptide complexes corresponding to the HLA type and one or more immunogenic peptides HLA-peptide complexes to the inert surface medium of the biological filter - production of HLA-peptide complexes comprising HLA proteins and immunogenic peptides - production of HLA-peptide complexes comprising recombinantly produced HLA proteins and synthetically produced immunogenic peptides Generating HLA-peptide complexes includes recombinantly produced HLA proteins and immunogenic peptides Endogenously obtained HLA-peptides from patients Collection of peptide complexes Examination of cerebrospinal fluid to identify immunogenic peptides Examination of cerebrospinal fluid to identify multiple immunogenic peptides Blood and cerebrospinal fluid analysis or tissue-specific disease HLA typing determined by identification of peptides determined by at least one of relevant peptide analysis Biological filters comprising one or more of sheet materials, liquids, mesh structures, fibers, gels, or beads Inert surface media containing one or more of polysulfone, polysulfone derivatives, glass matrix, silicon matrix, polydimethylsiloxane (PDMS), polycarbonate, polyetherimide (Ultem), or tritane Polyethylene glycol (PEG) or PEG derivatives, polystyrene, An inert surface medium containing one or more of avidin or streptavidin HLA-peptide complexes covalently attached to an inert filter surface via a maleimide analogue Binding to an inert surface medium to capture pathogenic cells Blood from the patient is flowed over the HLA-peptide complexes that cause leukemia, acute leukemia, cancer, myasthenia gravis (MG), Lambert-Eaton syndrome, multiple sclerosis (MS), polycythemia vera (PC, Use of biological filters to trap pathogenic cells associated with at least one of PCV), thrombocytosis, scleroderma, type 1 diabetes, psoriasis, Crohn's disease, or multiple sclerosis Bone marrow proliferation blood from the patient on the HLA-peptide complex bound to an inert surface medium, further comprising capturing pathogenic cells associated with at least one of a sexually transmitted disease or a viral, bacterial, fungal, or parasitic infection. identification of said one or more immunogenic peptides comprises comparing the peptides to a database of disease-associated immunogenic peptides and their binding affinities to corresponding HLAs said HLA types are HLA I and is HLA II A method comprising identifying the patient's human leukocyte antigen (HLA) type Identification of one or more immunogenic peptides associated with the patient's disease Corresponding to the patient's identified HLA type Recombinantly or endogenously produced HLA proteins binding HLA proteins to an inert surface medium Synthesis of one or more identified peptides associated with the patient's disease HLA bound to an inert surface medium Loading of identified peptides on proteins Simultaneous loading of HLA proteins bound to an inert surface medium loading and binding Sequential loading and binding of HLA proteins bound to an inert surface medium Identification of specific disease-associated peptides that induce T-cell receptor activation in patients with identified HLAs T to filter exposing the patient's blood to a filter composed of the identified HLA-loaded disease-associated peptide complexes for cell binding exposing the blood to the patient after removing the bound T cells binding Exposing filters containing depleted T cells to a separation agent to remove T cells and counting depleted T cells Counted T cells using flow cytometry including fluorescence-activated cell sorting (FACS) Counted Estimation of disease progression based on measured T cell counts Modification of patient treatment based on T cell counts Linking of HLA-peptide complexes to detectable labels Fluorophores, enzymes, radioisotopes, heavy metals, or nuclei Linking the HLA-peptide complex to a label containing one or more of the magnetic resonance markers Administering an anticoagulant during biological filtration Identifying one or more immunogenic peptides associated with the patient's disease Comparison of one or more of the identified immunogenic peptides to databases of disease-associated immunogenic peptides and their binding affinities to corresponding HLA types in patients Recombinantly to synthetically produced peptides Conjugation of produced HLA peptides Conjugation of HLA proteins with recombinantly produced peptides HLA proteins and peptides obtained endogenously from patients and used to make biological filters Biology Specific disease-related peptides incorporated into biological filters are associated with autoimmune diseases, cancer, or any other disease, including adaptive cell-mediated immune responses Disease-related peptides incorporated into biological filters are common Associated with sclerosteosis HLA monomers or multimers in biological filters HLA types are identified by blood analysis Biological filters designed to capture at least one of CD4+ or CD8+ cells Filters Performing biological filtration on the patient several times a year Enriching the blood with nutrients or pharmaceutical compositions before returning the biologically filtered blood to the patient , obtaining human leukocyte antigen (HLA)-peptide complex data for a specific patient with an autoimmune disease not induced by a second T cell HLA-peptide complex data for a specific patient and T cell-associated pathology H associated with patient populations with A comparison to the LA-peptide complex data, where the population data show that individuals with an autoimmune disease induced by a first T cell were treated over time as induced by a second T cell. remove a second T cell from the patient before the autoimmune disease in a given patient is caused by a second T cell that is not currently causing the disease Acquisition of HLA-peptide complex data for a given patient includes HLA typing and analysis of related peptides HLA type is identified by blood analysis and peptide analysis can be cerebrospinal fluid analysis or tissue-specific Performed by at least one of the disease-associated peptide assays Analysis of associated peptides includes examination of cerebrospinal fluid Comparing specific patient HLA-peptide complex data with patient populations with T cell-associated pathologies Comparing with relevant HLA-peptide complex data, comparing disease-related parameters including age from onset, symptoms, and treatment, HLA typing analysis, and analysis of peptides presented by corresponding HLA proteins. Comparing HLA-peptide complex data for a specific patient with HLA-peptide complex data relevant to a patient population with T cell-related pathology, comparing patients sharing each other's HLA types Intermolecular or intramolecular epitope spreading Identifying three or more T-cell populations that can cause autoimmune disease and removing them before they cause disease Autoimmune disease in a given patient Remove T cells of additional T cell populations from a particular patient before they are triggered by additional T cell populations Adjust patient treatment based on identified secondary T cells Remove secondary T cells involves the binding of HLA-peptide complexes to T-cell receptors on secondary T-cells The autoimmune disease is multiple sclerosis, in which T-cells contain myelin or aquaporin channels in the non-myelinic central nervous system Myelin is activatable against system proteins Myelin is myelin oligodendrocyte glycoprotein (MOG), myelin basic protein (MBP), myelin proteolipid protein (PLP), opaline protein, oligodendrocyte-specific contain one or more proteins (OSP), myelin-associated glycoprotein (MAG) remove two or more types of T cells using a biological filter Simultaneous removal of cells Removal of cells of additional T-cell populations includes binding of HLA-peptide complexes to T-cell receptors of cells of additional T-cell populations Cells of said additional T-cell populations is removed by a biological filter Simultaneous elimination of primary T cells, secondary T cells, and additional T cell populations Additional T cell populations predicted to cause damage in the future - stripping native peptides from the first group of human leukocyte antigens (HLA) in a first biological fluid sample; - sequencing one or more of the stripped native peptides; Comparison of one or more peptide sequences stripped and removed from the patient with known information to determine one or more disease-specific peptide sequences among native peptides Multiple HLA-peptide complexes loading a second group of HLAs, a plurality of peptides sharing one or more disease-specific peptide sequences to form a plurality of HLA-peptide complexes in contact with a second biological fluid sample; Measure the amount of T cells that bind to multiple HLA-peptide complexes for multiple HLA-peptide complexes contacted with 2 biological fluid samples Measured T that binds multiple HLA-peptide complexes Estimate the amount of disease-specific pathogenic T cells in the biofluid volume within the patient based on the amount of cells Before measuring the amount of T cells that bind to multiple HLA-peptide complexes, Measure, estimate, or predict the binding affinity of each of multiple HLA-peptide complexes to pathogenic T cells Validate that the correct disease-specific pathogenic T cells bind multiple HLA-peptide complexes Assessment of disease state based on the determined amount of T cells that bind to multiple HLA-peptide complexes The measured amount of T cells that bind to multiple HLA-peptide complexes and the population of patients with disease Comparison of the amount of T cells measured from Evaluate the efficacy of a disease treatment regimen by comparing the amount of measured T cells that bind multiple HLA-peptide complexes with previously measured amounts of T cells that bind multiple HLA-peptide complexes Adjusting the treatment regimen based on comparison with the amount of T-cells that have been treated. Generation of biological filters containing multiple HLA-peptide complexes. creating a biological filter comprising synthesizing a plurality of peptides sharing a specific sequence, further synthesizing HLA, synthesizing the synthesized HLA sharing one or more disease-specific sequences forming a synthesized HLA-peptide complex by mixing with a plurality of peptides that have been synthesized; and applying the synthesized HLA-peptide complex to an inert surface medium. Detectable markers include one or more of fluorophores, enzymes, radioisotopes, heavy metals, and nuclear magnetic resonance markers Multiple HLA-peptide complexes are associated with one or more disease-specific sequences The HLA-peptide complex contains multiple synthetically or recombinantly produced/engineered peptides that share one or more disease-specific sequences, or multiple peptides that are endogenously obtained from the patient. Use mass spectrometry to identify one or more sequences of stripped native peptides Identify T cell binding to multiple HLA-peptide complexes amount is measured using flow cytometry a certain amount of T cells that bind multiple HLA-peptide complexes have multiple peptides that share one or more disease-specific peptide sequences multiple A certain amount of T cells that bind to the HLA-peptide complex contain multiple peptides that share multiple disease-specific peptide sequences If the patient has multiple sclerosis, said one or more disease-specific peptides The sequences are sequences of peptides derived from myelin-associated proteins If the patient has type 1 diabetes, the one or more disease-specific peptide sequences are sequences of insulin peptides, or other proteins associated with beta-cell proteins If the patient has myasthenia gravis, the one or more disease-specific peptide sequences are those of an acetylcholine receptor peptide If the patient has Crohn's disease, the one or more disease-specific peptides The sequence is that of a gut peptide The biological fluid is whole blood, blood fraction, cerebrospinal fluid, synovial fluid, alveolar lavage, peritoneal lavage, lymph, or bone marrow

Other embodiments will be apparent from consideration of the specification and embodiments disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosed embodiments being indicated by the following claims.

Claims (195)

A biological filter characterized by comprising:
Inert surface media.
A human leukocyte antigen (HLA) protein disposed on said inert surface medium.
an antigenic peptide bound to said HLA protein on said inert surface medium.
Said antigenic peptide and said HLA protein are selected when a T cell contacts the complex to allow antigen-specific T cell receptors to bind to said complex of said antigenic peptide and said HLA protein. , thereby immobilizing specific T cells to said inert surface medium via the complex. 2. The filter of claim 1, wherein the inert surface medium comprises sheet material, mesh structures, fibers, gels, liquids, or beads. 2. The filter of claim 1, wherein the inert surface medium comprises polysulfone or polysulfone derivatives, glass matrix, silicon matrix, polydimethylsiloxane (PDMS), polycarbonate, polyetherimide (Ultem), or tritan. 4. The filter of claim 3, wherein said inert surface medium comprises said polysulfone. 5. The filter of claim 4, wherein said inert surface medium further comprises a polyelectrolyte. 2. The filter of claim 1, wherein said HLA proteins are disposed on said inert surface medium via covalent binding, non-covalent interactions or adsorption. 7. The filter of claim 6, wherein said HLA proteins are arranged on said inert surface medium via covalent binding, non-covalent interactions or adsorption. A filter according to claim 1, characterized in that said inert surface medium comprises polyethylene glycol (PEG) or PEG derivatives, polystyrene, avidin and/or streptavidin. 2. The filter of claim 1, wherein the HLA proteins are arranged on the inert surface medium such that their anchor positions are spaced apart from each other by at least the width of the HLA binding groove. 2. The filter of claim 1, wherein said HLA protein comprises one or more monomers or multimers. 2. The filter of claim 1, wherein said HLA protein is truncated. 2. The filter of claim 1, wherein said HLA protein is engineered to contain a cysteine as a C-terminal residue. 13. The filter of claim 12, wherein said C-terminal cysteine is linked to the HLA protein via a peptide linker. 2. A filter according to claim 1, characterized in that said HLA proteins are HLA I and/or HLA II. 2. The filter of claim 1, wherein said HLA proteins are HLA typed to match the patient. wherein said antigenic peptides are synthetically produced and loaded onto said HLA proteins to form HLA-peptide complexes capable of selectively binding to said antigen-specific T cell receptors. Term 1 filter. 2. The filter of claim 1, wherein said HLA protein is recombinantly produced. 2. The filter of claim 1, wherein said antigenic peptide is derived from a protein associated with multiple sclerosis. The antigenic peptide is a myelin oligodendrocyte glycoprotein (MOG), a myelin basic protein (MBP), a myelin proteolipid protein (PLP), an opaline protein, an oligodendrocyte-specific protein (OSP), a myelin-associated glycoprotein ( MAG), or a combination thereof. The antigen peptide is MBP _87-99 , MBP _85-99 , MBP _83-96 , MBP _217-231, MBP _88-102, MBP _282-296, PLP _91-110, PLP _131-151, PLP _283-252, PLP _263-277, PLP _58-72, PLP _13-27, OPALIN _46-60, OPALIN _27-41, OPALIN _127-141, MOG _210-224, MOG _29-43, MOG _176-190, MOG _225-239, 20. The filter of claim 19, wherein the filter is OSP _74-88 , OSP _114-128, MAG _8-22, MAG _467-481, MAG _529-543 , or combinations thereof. 3. The filter of claim 1, wherein the filter comprises multiple layers configured to allow fluid flow between the filters. A filter that is a biological filter for cytoreduction of multiple sclerosis-associated T cells, including:
A filter medium as a host material that selectively binds to said antigen-specific T-cell receptors.
The host material comprises a human leukocyte antigen (HLA)-myelin-peptide complex and is selected to bind to a myelin-specific T-cell receptor, thereby generating a population of T cells that recognize the HLA-myelin peptide complex. It is characterized by enabling specific binding. 23. The filter of claim 22, wherein said HLA-myelin-peptide complexes each comprise said antigenic peptide and said HLA protein. 23. The filter of claim 22, wherein said filter medium comprises an inert surface. 23. The filter of claim 22, wherein said filter medium comprises said beads. 23. The filter of claim 22, wherein said filter media comprises said sheet material. 23. The filter of Claim 22, wherein said filter medium comprises a fluid. 4. The claim wherein said filter media comprises said polysulfone or said polysulfone derivative, said glass matrix, said silicon matrix, said polydimethylsiloxane (PDMS), said polycarbonate, said polyetherimide (Ultem), or said tritane. 23. The filter of paragraph 22. 29. The filter of claim 28, wherein said filter medium further comprises said polyelectrolyte. 23. The filter of claim 22, wherein said HLA-myelin-peptide complexes are disposed on said inert surface medium via covalent bonding, non-covalent interactions or adsorption. 23. The filter of claim 22, wherein said HLA-myelin-peptide complexes are disposed on said medium via a maleimide analogue. 25. The filter of claim 24, wherein said inert surface comprises said polyethylene glycol (PEG) or said PEG derivative, said polystyrene, said avidin and/or said streptavidin. 23. A filter according to claim 22, wherein the HLA-myelin-peptide complexes are arranged on the filter medium such that complex anchor positions are spaced from each other by at least the width of the HLA binding groove. . 23. The filter of claim 22, wherein said HLA proteins are truncated. 23. The filter of claim 22, wherein said HLA protein is engineered to contain said cysteine as a C-terminal residue. 36. The filter of claim 35, wherein said C-terminal cysteine is linked to the HLA protein via said peptide linker. 23. The filter of claim 22, wherein said HLA proteins are said HLA I and/or said HLA II. 23. The filter of claim 22, wherein said HLA proteins are HLA typed to match the patient. said myelin peptides comprising: said myelin oligodendrocyte glycoprotein (MOG), said myelin basic protein (MBP), said myelin proteolipid protein (PLP), said opaline protein, said oligodendrocyte specific protein (OSP), 23. The filter of claim 22, wherein said filter is derived from said myelin-associated glycoprotein (MAG), or a combination thereof. The antigen is the MBP _87-99 , the MBP 85-99 , the MBP _83-96 , the MBP _{217-231 , the} MBP _{88-102, the} MBP _{282-296, the} PLP _{91-110, the} PLP _{131- 151,} said PLP _283-252, said PLP _263-277, said PLP _58-72, said PLP _13-27, said OPALIN _46-60, said OPALIN _27-41, said OPALIN _127-141, said MOG _210-224, said MOG _29-43, said MOG _176-190, said MOG _225-239, said OSP _74-88 , said OSP _114-128, said MAG _8-22, said MAG _467-481, said MAG _529-543 , or 40. A filter according to claim 39, characterized in that it is a combination of 23. The filter of claim 22, wherein said filter comprises a plurality of said layers configured for fluid flow between the filters. 23. The filter of claim 22, wherein said host material further comprises a complex of said HLA protein and said antigenic peptide derived from a non-myelinic multiple sclerosis-associated protein. A device for removing pathogenic T cells from a patient's blood, the device comprising:
A first stage area configured to hold an inlet, a leukocyte outlet, and a blood separation device that permits the return of other fractions into the patient and is capable of separating leukocytes from other fractions of whole blood.
A first pump for pumping blood from the patient through the first stage region.
configured to retain said biological filter comprising said human leukocyte antigen (HLA)-peptide complex, having one or more said inlets and one or more said outlets, and A second stage area oriented to allow flow from the leukocyte outlet of the blood separation device to the one or more inlets of the biological filter.
A second pump for recirculating the leukocytes from the one or more outlets of the biological filter to the one or more inlets of the biological filter.
A plurality of electrically controllable valves for directing blood through the first stage area and the second stage area.
One or more processors configured as follows:
The first pump is controlled to cause blood flow through the first stage area until a certain amount of the white blood cells are separated and delivered to the second stage area.
Disabling the first pump when a certain amount of the white blood cells are separated and transported to the second stage area.
activating the second pump and controlling a plurality of the valves to regenerate an amount of the white blood cells through the biological filter for a time sufficient to separate the pathogenic T cells from non-pathogenic white blood cells; Circulate.
The non-pathogenic white blood cells are returned to the patient. The electrically controllable plurality of valves return the white blood cells to the patient while the second pump is activated to recirculate the white blood cell mass through the biological filter in a second stage. 44. The apparatus of claim 43, comprising one or more of said valves controllable by said one or more processors to prevent . The electrically controllable plurality of valves causes the leukocytes to enter the first stage while a second pump is activated to recirculate the amount of the leukocytes through the biological filter in the second stage. 44. The apparatus of claim 43, comprising one or more of said valves controllable by said one or more processors to prevent movement from a region to said second stage region. The one or more processors control the plurality of electrically controllable valves to cause the white blood cells to be processed in batches in the second stage area, and the first batch of white blood cells to be processed in the second stage area. configured to recirculate and then return to the patient before allowing said one or more processors to enter said second batch of leukocytes into said biological filter in a second stage. 44. The apparatus of claim 43, wherein 44. The apparatus of claim 43, wherein said blood separation device is configured to separate blood using apheresis. 44. The apparatus of claim 43, wherein said blood separation device is configured to separate blood using centrifugation. 44. The apparatus of claim 43, wherein said blood separation device is configured to separate blood using filtration. 44. The device of claim 43, wherein said blood separation device is configured to mechanically bind said leukocytes to a cell-specific matrix. 44. The apparatus of claim 43, wherein the blood separation device is configured to allow binding of cell-specific antibodies to the leukocytes. Further comprising the blood mixing device, wherein the one or more processors control the blood mixing device to mix other fractions of whole blood and/or the non-pathogenic white blood cells prior to return to the patient. 44. The apparatus of claim 43, wherein the apparatus is configured to: 44. The device of claim 43, wherein said biological filter comprises said plurality of layers with said human leukocyte antigen (HLA)-peptide complex in each layer. wherein said second stage area is sized such that said biological filter can contain about 3-50 ml of the fraction collected in said first pump. 44. Apparatus according to paragraph 43. 44. The apparatus of claim 43, wherein said peristaltic pump is at least one of said first pump and said second pump. 44. The apparatus of claim 43, further comprising a blood storage chamber, wherein blood from a patient is stored in said blood storage chamber prior to separation within said blood separation device. 44. The apparatus of claim 43, further comprising an arterial pressure control unit. wherein said one or more processors are configured to control said one or more valves to add red blood cells and saline prior to returning another fraction of whole blood to the patient. 44. The device of claim 43. 44. The apparatus of claim 43, wherein the one or more processors are configured to control the one or more valves to deliver anticoagulant to the second stage area. 44. The device of claim 43, wherein said biological filter is configured to selectively bind said pathogenic T cells. A tubing set for removing said pathogenic T-cells from the blood of a patient, characterized in that it comprises:
A first stage area comprising said blood separation device used to separate said white blood cells from other fractions of whole blood and having said inlet, said white blood cell outlet and a blood fraction outlet.
A biological system comprising said human leukocyte antigen (HLA)-peptide complex and having one or more primary inlets, one or more primary outlets, one or more recirculation inlets, and one or more recirculation outlets A second stage area containing a filter.
A recirculation loop interconnecting one or more of said recirculation outlets and said recirculation inlets.
One or more blood suction tubes for carrying blood from a patient to said one or more inlets of said first stage area.
One or more intermediate tubes configured to carry blood from the leukocyte outlet of the first stage area to the primary inlet of the second stage area.
One or more first stage bypass tubes configured to carry the blood fraction from the blood fraction outlet of the first stage region for return to the patient.
One or more leukocyte return tubes configured to transport the leukocytes from the primary outlet of the second stage area for return to the patient. 62. A tubeset according to claim 61, wherein said primary inlet of said second stage area and said recirculation inlet of said second stage area are common. 62. A tubeset according to claim 61, wherein said primary outlet of said second stage area and said recirculation outlet of said second stage area are common. A system characterized by the predictive adjustment of therapeutic regimens for patients with T cell-associated immune disorders, comprising:
One or more processors configured as follows:
configured to receive first data relating to treatment of a plurality of patients sharing a common HLA and common peptides that cause disease-associated T-cell activation, and in further progression of the disease, a greater number of different peptides , which activates the disease-associated T cells more than at earlier time points, the first data include the progression of common peptides that activate T cells over time.
A first set of peptides activates a first subpopulation of said disease-associated T cells and a second set of peptides activates a second subpopulation of said disease-associated T cells, having a common HLA and a common peptide receive second data relating to a particular patient at a stage of non-modifiable disease;
Using the first data, it is determined that the second set of peptides in a particular patient corresponds to further progression of the disease.
Before said second set of peptides activates said second subpopulation of disease-associated T cells, remedial action is taken to remove said second set of peptides from a particular patient. 65. The system of Claim 64, wherein said remedial action comprises outputting instructions to remove said second subpopulation of disease-associated T cells from a particular patient. 65. The system of Claim 64, wherein said remedial action comprises outputting information for use in constructing said filter comprising said second set of peptides. 65. The system of claim 64, wherein said second data is determined by analyzing information regarding HLA typing and related peptides. 68. The system of claim 67, wherein said analyzing step comprises stripping said peptides from said HLA complex and determining peptide sequences. 68. The system of claim 67, wherein said HLA typing is based on blood analysis and said information about peptides is based on analysis of tissue-specific and disease-related biological fluids. 68. The system of claim 67, wherein said analyzing step comprises analyzing cerebrospinal fluid peptide data. The identification of said second set of peptides corresponding to further progression of said disease is a comparison of disease-related parameters including years from onset, Neurological Symptom Scale (EDSS) and treatment, HLA typing analysis and corresponding said HLA proteins. 65. The system of claim 64, comprising analyzing the peptides presented by. 65. The system of claim 64, wherein said first set of peptides and said second set of peptides are variants of the same peptide. 65. The system of claim 64, wherein said first peptide set and said second peptide set are different from each other. 65. The system of claim 64, wherein said one or more processors are configured as follows.
Additional common peptide sets are identified that do not activate additional subpopulations of said disease-associated T cells.
Determine that said additional peptide sets correspond to further progression of the disease.
Before said additional peptide set activates said additional subpopulation of disease-related T cells, said remedial action is taken to deplete said additional subpopulation of disease-related T cells from the patient. 75. The system of claim 74, wherein said remedial action comprises outputting instructions to eliminate said additional subpopulation of said disease-associated T cells. 75. The system of Claim 74, wherein said remedial action comprises outputting data for use in constructing said filter comprising said additional set of peptides. 75. The system of claim 74, wherein the one or more processors are further configured to adjust patient therapy based on the identified additional peptide sets. 65. The system of claim 64, further comprising adjusting treatment of the patient based on the identified second set of peptides. 65. The system of claim 64, wherein said remedial action is taken to simultaneously eliminate said first subpopulation of disease-associated T cells and said second subpopulation of disease-associated T cells. wherein said ameliorative action is taken simultaneously to said first subpopulation of disease-related T cells, said second subpopulation of disease-related T cells, and said additional subpopulation of disease-related T cells. 75. The system of claim 74. 65. The system of claim 64, wherein said immune disease is multiple sclerosis and said T cells can be activated against non-myelin central nervous system proteins including said myelin or aquaporin channels. said myelin comprises said myelin oligodendrocyte glycoprotein (MOG), said myelin basic protein (MBP), said myelin proteolipid protein (PLP), said opaline protein, said oligodendrocyte specific protein (OSP) 82. The system of claim 81, comprising myelin-associated glycoprotein (MAG), or a combination thereof. the peptide is the MBP _87-99 , the MBP 85-99 , the MBP _83-96 , the MBP _{217-231 , the} MBP _{88-102, the} MBP _{282-296, the} PLP _{91-110, the} PLP _{131- 151,} said PLP _283-252, said PLP _263-277, said PLP _58-72, said PLP _13-27, said OPALIN _46-60, said OPALIN _27-41, said OPALIN _127-141, said MOG _210-224, said MOG _29-43, said MOG _176-190, said MOG _225-239, said OSP _74-88 , said OSP _114-128, said MAG _8-22, said MAG _467-481, said MAG _529-543 , or 83. The system of claim 82, wherein a combination of A method of removing specific T cells, pathogenic cells, or non-pathogenic cells from a patient, characterized by comprising:
Collection of said biological fluid containing specific cells from a patient.
Extracorporeal flow of said biological fluid through a media host material that selectively binds only to specific cells in order to entrap specific cells in the media.
Returning the biological fluid to the patient, excluding the specific cells that have been entrapped. 85. The method of claim 84, wherein said biological fluid comprises at least one of whole blood or blood fractions. 85. The method of claim 84, wherein said biological fluid comprises cerebrospinal fluid. 85. The method of claim 84, wherein said biological fluid comprises bone marrow. 85. The method of claim 84, wherein said biological fluid comprises synovial fluid. 85. The method of claim 84, wherein said biological fluid comprises fluid obtained from alveolar lavage. 85. The method of claim 84, wherein said biological fluid comprises ascites fluid. 85. The method of claim 84, wherein said medium comprises said inert surface. 92. The method of claim 91, wherein said inert surface comprises said polyethylene glycol (PEG) or said PEG derivative, said polystyrene, said avidin and/or said streptavidin. The medium comprises one or more of the polysulfone or the polysulfone derivative, the glass matrix, the silicon matrix, the polydimethylsiloxane (PDMS), the polycarbonate, the polyetherimide (Ultem), or the tritane. 85. The method of claim 84. 94. The method of claim 93, wherein said medium comprises said polysulfone. 95. The method of claim 94, wherein said filter medium further comprises said polyelectrolyte. 85. The method of claim 84, wherein said medium comprises one or more of said sheet material, said liquid, said mesh structure, said fibers, said gel, or said beads. 85. The method of claim 84, wherein said material comprises said human leukocyte antigen (HLA)-peptide complexes, each HLA-peptide complex comprising said HLA protein and said peptide. 98. The method of claim 97, wherein said HLA proteins comprise said HLA I and/or said HLA II or truncated forms thereof. 98. The method of claim 97, wherein said HLA is further engineered to contain a cysteine residue at said C-terminus. 100. The filter of claim 99, wherein said C-terminal cysteine is linked to said HLA protein via said peptide linker. 98. The method of claim 97, wherein said HLA-peptide complex is disposed on said medium via said maleimide analogue. 85. The method of claim 84, wherein said substance comprises an antibody. 85. The method of claim 84, wherein the biological fluid is circulated through the medium and returned to the patient using the peristaltic pump. 85. The method of Claim 84, wherein said medium comprises a fluid. 85. The method of claim 84, wherein said specific T cells comprise one or more of CD4+ cells or CD8+ cells. 85. The method of claim 84, wherein said T cells comprise T cell receptors specific for said antigenic peptides derived from proteins associated with autoimmune diseases. 107. The method of claim 106, wherein said autoimmune disease is multiple sclerosis. 85. The method of claim 84, wherein said pathogenic cells are associated with cancerous diseases, including hematologic or solid tumors. A method for creating said personalized biological filter for selectively removing said pathogenic T cells from a patient, comprising:
Identification of the patient's human leukocyte antigen (HLA) type.
Identification of said one or more immunogenic peptides associated with the patient's disease.
Said HLA-peptide complex produced/made recombinantly, synthetically or endogenously corresponding to said patient's determined HLA type and said one or more immunogenic peptides.
Binding of the HLA-peptide complex to the inert surface medium of the biological filter. 110. The method of claim 109, wherein said HLA-peptide complex comprises said HLA protein and said immunogenic peptide. 111. The method of claim 110, wherein said HLA-peptide complex comprises said recombinantly produced HLA protein and said immunogenic peptide made synthetically. 111. The method of claim 110, wherein said HLA-peptide complex comprises said recombinantly produced HLA protein and said immunogenic peptide. 111. The method of claim 110, wherein said HLA-peptide complex is obtained endogenously from a patient. 110. The method of claim 109, wherein identifying the one or more immunogenic peptides comprises examining cerebrospinal fluid. 110. The method of claim 109, wherein said one or more immunogenic peptides comprises multiple immunogenic peptides. 110. The method of claim 109, wherein said HLA typing is identified by said blood analysis and said peptide identification is determined by either cerebrospinal fluid analysis or tissue-specific disease-associated peptide analysis. 110. The method of Claim 109, wherein said filter comprises one or more of said sheet material, said liquid, said mesh structure, said fibers, said gel, or said beads. said inert surface medium comprising one or more of said polysulfone or said polysulfone derivative, said glass matrix, said silicon matrix, said polydimethylsiloxane (PDMS), said polycarbonate, said polyetherimide (Ultem), or said tritane. 110. The method of claim 109, characterized by: 119. The method of claim 118, wherein said inert surface medium comprises said polysulfone. 120. The method of Claim 119, wherein said inert surface medium further comprises said polyelectrolyte. 110. The method of claim 109, wherein said inert surface medium comprises at least one of said polyethylene glycol (PEG) or said PEG derivative, said polystyrene, said avidin and/or said streptavidin. 110. The method of claim 109, wherein said HLA-peptide complexes are attached to said inert surface medium via at least one of covalent bonds, non-covalent interactions or adsorption. 123. The method of claim 122, wherein said HLA-peptide complex is covalently attached to said inert filter surface via said maleimide analogue. 110. The method of Claim 109, wherein the filter comprises the plurality of layers configured to allow fluid flow between the filters. 110. The method of claim 109, further comprising flowing blood from a patient over said HLA-peptide complex bound to said inert surface medium, thereby trapping pathogenic cells. The pathogenic cell is leukemia, acute leukemia, cancer, myasthenia gravis (MG), Lambert-Eaton syndrome, multiple sclerosis (MS), polycythemia vera (PC, PCV), thrombocytosis, scleroderma 126. The method of claim 125, wherein the method is associated with at least one of: disease, type 1 diabetes, psoriasis, Crohn's disease, or multiple sclerosis. Flowing blood from said patient over said HLA-peptide complex bound to said inert surface medium, thereby associated with at least one of a myeloproliferative disease or a viral, bacterial, fungal, or parasitic infection 110. The method of claim 109, further comprising capturing said pathogenic cells that do. 4. The step of identifying said one or more immunogenic peptides comprising comparing said peptides to a database of disease-associated immunogenic peptides and their binding affinities for the corresponding HLA. 109. The method of paragraph 109. 110. The method of claim 109, wherein said HLA type is HLA I and/or HLA II. A method for creating said personalized biological filter for selectively removing said pathogenic T cells from a patient, comprising:
Identification of the patient's human leukocyte antigen (HLA) type.
Identification of said one or more immunogenic peptides associated with the patient's disease.
said recombinantly or endogenously produced HLA protein corresponding to said identified HLA type of the patient.
Binding of said HLA proteins to said inert surface medium.
Synthesis of said identified one or more peptides associated with the patient's disease.
Loading of the identified peptides on the HLA proteins bound to the inert surface medium. 131. The method of claim 130, wherein said loading and binding occur sequentially. 131. The method of claim 130, wherein said loading and binding occur substantially simultaneously. A method of treating a patient, characterized by comprising:
Identification of the patient's human leukocyte antigen (HLA) type.
Identification of specific disease-associated peptides that induce T-cell receptor activation in patients with the identified HLA.
For T cell binding to the filter, the patient's blood is exposed ex vivo to the filter composed of the identified HLA-loaded complexes with the disease-associated peptide.
The blood, which has had the bound T cells removed, is returned to the patient. 134. The method of claim 133, further comprising exposing said filter containing bound T cells to a separating agent to remove T cells, and counting the removed T cells. 135. The method of claim 134, wherein said T cells are counted using flow cytometry, including fluorescence activated cell sorting (FACS). 135. The method of claim 134, further comprising estimating disease progression based on the counted number of T cells. 135. The method of claim 134, further comprising altering patient therapy based on the counted T cell count. 134. The method of claim 133, wherein said HLA-peptide complex is linked to a detectable label. 139. The method of claim 138, wherein said label comprises one or more of fluorophores, enzymes, radioisotopes, heavy metals, or nuclear magnetic resonance markers. 134. The method of claim 133, further comprising administering said anticoagulant to the patient. 134. The method of claim 133, wherein identifying said specific disease-associated peptide comprises:
Identification of said one or more immunogenic peptides associated with the patient's disease.
Comparison of one or more of said immunogenic peptides identified with said database of disease-associated immunogenic peptides and their binding affinities for said corresponding HLA types in patients. 134. The method of claim 133, wherein said HLA protein is recombinantly produced and said peptide is produced synthetically. 134. The method of claim 133, wherein said HLA proteins and peptides are produced recombinantly. 134. The method of claim 133, wherein said HLA proteins and peptides are obtained endogenously from a patient. 134. The method of claim 133, wherein said specific disease-associated peptide is associated with an autoimmune disease, cancer, or any other disease involving an adaptive cellular immune response. 146. The method of claim 145, wherein said specific disease-associated peptide is associated with multiple sclerosis. 134. The method of claim 133, wherein said HLA is said monomer or said multimer. 134. The method of claim 133, wherein said HLA typing is determined by said blood analysis. 134. The method of claim 133, wherein said HLA is said HLA I and/or said HLA II. 134. The method of claim 133, wherein said T cells comprise at least one of said CD4+ cells or said CD8+ cells. 134. The method of claim 133, wherein said method is performed on the patient several times per year. 134. The method of claim 133, further comprising enriching the blood with nutrients or pharmaceutical compositions prior to returning the blood to the patient. A method for treating a patient with a T cell-associated autoimmune disease, characterized by comprising:
Acquisition of said human leukocyte antigen (HLA)-peptide complex data for a particular patient with an autoimmune disease induced by a first T cell and not by a second T cell.
Comparison of HLA-peptide complex data for a particular patient with said HLA-peptide complex data associated with a patient population with T-cell related pathology. Here, population data provide epitope spreading information suggesting that individuals with an autoimmune disease induced by said first T cell progress over time as induced by said second T cell. include.
The second T cells are removed from the particular patient before the particular patient's autoimmune disease is caused by the second T cells. 154. The method of claim 153, wherein obtaining said HLA-peptide complex data for said particular patient comprises analyzing said HLA typing and said related peptides. 155. The method of claim 154, wherein analyzing said related peptides comprises said stripping peptides from said HLA-peptide complexes and determining said peptide sequences. 155. The method of claim 154, wherein said HLA typing is determined by said blood analysis and said peptide analysis is performed by either said cerebrospinal fluid analysis or said tissue-specific disease-associated peptide analysis. Method. 155. The method of claim 154, wherein analyzing said related peptides comprises examining said cerebrospinal fluid. Comparing the HLA-peptide complex data of the particular patient with the HLA-peptide complex data associated with a patient population having T-cell related pathology includes age from onset, symptoms, and treatment. 154. The method of claim 153, comprising comparison of disease-related parameters, said HLA typing analysis, and analysis of peptides presented by corresponding HLA proteins. Comparing the HLA-peptide complex data of the particular patient and the HLA-peptide complex data associated with a patient population having a T-cell associated pathology compares patients sharing the HLA types with each other. 154. The method of claim 153, comprising: 154. The method of claim 153, wherein said epitope spreading is intramolecular. 154. The method of claim 153, wherein said epitope spreading is intermolecular. 154. The method of claim 153, comprising:
Identification of additional T-cell populations that may cause autoimmune disease over time.
T cells of the additional T cell population are removed from the particular patient before the autoimmune disease of the particular patient is caused by the additional T cell population. 154. The method of claim 153, further comprising adjusting patient therapy based on said second T cells identified. 154. The method of claim 153, wherein depleting said second T cell comprises binding said HLA-peptide complex to a T cell receptor of said second T cell. 154. The method of claim 153, wherein said autoimmune disease is multiple sclerosis and T cells are activatable against said non-myelin central nervous system proteins including said myelin or said aquaporin channels. . said myelin comprises said myelin oligodendrocyte glycoprotein (MOG), said myelin basic protein (MBP), said myelin proteolipid protein (PLP), said opaline protein, said oligodendrocyte specific protein (OSP) 166. The method of claim 165, comprising one or more myelin-associated glycoproteins (MAGs). 154. The method of claim 153, wherein said second T cells are removed by said biological filter. 154. The method of claim 153, further comprising depleting said first T cell and said second T cell simultaneously. 163. The method of claim 162, wherein removing cells of said additional T-cell population comprises binding said HLA-peptide complexes to T-cell receptors of cells of said additional T-cell population. 163. The method of claim 162, wherein cells of said additional T cell population are removed by said biological filter. 163. The method of claim 162, further comprising simultaneously depleting cells of said first T cell, said second T cell, and said additional T cell population. 163. The method of claim 162, further comprising adjusting patient therapy based on said additional T cell populations identified. A method of estimating the amount of disease-specific pathogenic T cells in a patient, characterized by comprising:
A first biological fluid sample is obtained from the patient.
Stripping native peptides from a first group of said human leukocyte antigens (HLA) in said first biological fluid sample.
Identification of one or more sequences of stripped native peptides.
The identified sequence or sequences are compared to known information to identify one or more disease-specific peptide sequences in the native peptide.
Loading said HLA into a second group of peptides sharing said one or more disease-specific peptide sequences to form multiple HLA-peptide complexes.
Contacting a plurality of said HLA-peptide complexes with a second biological fluid sample.
For the plurality of HLA-peptide complexes contacted with the second biological fluid sample, the amount of T cells that bind to the plurality of HLA-peptide complexes is measured.
Based on the measured amount of T cells that bind to the plurality of HLA-peptide complexes, the amount of disease-specific pathogenic T cells in the biofluid volume within the patient is estimated. measuring, estimating, or determining the binding affinity of each of said plurality of HLA-peptide complexes to said disease-specific pathogenic T cells prior to measuring the amount of T cells that bind said plurality of HLA-peptide complexes; 174. The method of claim 173, further comprising predicting. 174. The method of claim 173, further comprising verifying that said disease-specific pathogenic T cells bind said plurality of HLA-peptide complexes. 174. The method of claim 173, further comprising assessing a disease state based on said measured amount of T cells that bind said plurality of HLA-peptide complexes. Assessing the disease state comprises comparing the measured amount of T cells that bind to the plurality of HLA-peptide complexes to the measured amount of T cells from a population of patients with the disease. 177. The method of claim 176, comprising: by comparing the measured amount of T cells binding to the plurality of HLA-peptide complexes with the previously measured amount of T cells binding to the plurality of HLA-peptide complexes, 174. The method of claim 173, further comprising evaluating efficacy of a therapeutic regimen of. based on a comparison of said measured amount of T cells that bind to said plurality of HLA-peptide complexes and said previously measured amount of T cells that bind to said plurality of HLA-peptide complexes, said 179. The method of claim 178, further comprising adjusting the therapeutic regimen. 174. The method of claim 173, further comprising producing said biological filter comprising said plurality of HLA-peptide complexes. 181. The method of claim 180, wherein creating said biological filter comprises synthesizing a plurality of said peptides that share one or more disease-specific sequences. said HLA synthesized by mixing HLA synthesized with a plurality of said peptides synthesized sharing said one or more disease-specific sequences; 182. The method of claim 181, further comprising forming a peptide complex and applying said synthesized HLA-peptide complex to said inert surface medium. 174. The method of claim 173, wherein said HLA is linked to a detectable marker. 184. The method of claim 183, wherein said detectable marker comprises one or more of said fluorophore, said enzyme, said radioisotope, said heavy metal, or said nuclear magnetic resonance marker. 174. The claim of claim 173, wherein said plurality of HLA-peptide complexes comprises a plurality of said synthetically or recombinantly produced/produced peptides sharing said one or more disease-specific sequences. Method. wherein said HLA-peptide complex comprises a plurality of said synthetically or recombinantly produced peptides that share said one or more disease-specific sequences or are endogenously obtained from a patient. 174. The method of claim 173. 174. The method of claim 173, wherein one or more sequences of said stripped native peptides are determined using a mass spectrometer. 174. The method of claim 173, wherein the amount of T cells that bind said plurality of HLA-peptide complexes is measured using flow cytometry. 174. The method of claim 173, wherein a quantity of T cells that bind said plurality of HLA-peptide complexes have said plurality of peptides sharing said one or more disease-specific peptide sequences. 174. The method of claim 173, wherein the amount of T cells that bind to said plurality of HLA-peptide complexes comprises said plurality of peptides sharing a plurality of disease-specific peptide sequences. 174. The method of claim 173, wherein if said patient has multiple sclerosis, said one or more disease-specific peptide sequences are sequences of peptides derived from myelin-associated proteins. 174. The method of claim 173, wherein if said patient has type 1 diabetes, said one or more disease-specific peptide sequences are sequences of insulin peptides or other proteins associated with beta-cell proteins. . 174. The method of claim 173, wherein if said patient has myasthenia gravis, said one or more disease-specific peptide sequences are those of an acetylcholine receptor peptide. 174. The method of claim 173, wherein if said patient has Crohn's disease, said one or more disease-specific peptide sequences are those of gastrointestinal peptides. 174. The method of claim 173, wherein said biological fluid is whole blood, a blood fraction, cerebrospinal fluid, synovial fluid, alveolar lavage, peritoneal lavage, lymph, or bone marrow.

Images